Systems and methods for the autonomous transition of an electric vertical takeoff and landing aircraft

ABSTRACT

A system for autonomous flight of an electric vertical takeoff and landing (eVTOL) aircraft. The system may include a fuselage, a plurality of laterally extending elements, a plurality of propulsors, a flight controller, and a pilot override switch. The plurality of laterally extending elements are attached to the fuselage. The plurality of propulsors is attached to the plurality of laterally extending elements. The flight controller is communicatively connected to the pilot override switch. The flight controller is configured to identify a flight transition point, initiate rotation about an axis of the fuselage a as function of the flight transition point, and terminate rotation once the desired flight angle is reached.

FIELD OF THE INVENTION

The present invention generally relates to the field of electricaircraft. In particular, the present invention is directed to a systemand method for the transition of an electric vertical takeoff andlanding (eVTOL) aircraft from vertical to horizontal flight using atilting fuselage.

BACKGROUND

The autonomous transition of eVTOL aircraft between vertical andhorizontal flight can be complicated and cause difficulties for pilotsto handle safely due to the different modes of flight involved.Combining the hovering performance of helicopters with the rotatingpropulsors will provide not only a smoother transition, but a moredesirable and safe flight experience for pilots.

SUMMARY OF THE DISCLOSURE

In an aspect a system for the autonomous transition of an electricvertical takeoff and landing (eVTOL) aircraft is provided. The systemgenerally includes a fuselage, a plurality of laterally extendingelements, a plurality of propulsors, and a flight controller. Thefuselage is attached to the eVTOL aircraft. The plurality of laterallyextending elements is secured to the fuselage. The plurality ofpropulsors are attached to the plurality of laterally extending elementsand are configured to rotate between a lift position and forward thrustposition. The flight controller is configured to identify a flighttransition point, initiate rotation about an axis of the fuselage, andterminate rotation once desired flight angle is reached. The system alsomay include a pilot override switch coupled to the flight controller.

In another aspect, a method for the autonomous transition of an electricvertical takeoff and landing (eVTOL) aircraft is provided. The methodmay include identifying, by the flight controller, a flight transitionpoint, initiating, by the flight controller, the rotation about an axisof the fuselage as a function of the flight transition point, andterminating, by the flight controller, the rotation once a desiredflight angle is reached, also as a function of the flight transitionpoint.

These and other aspects and features of non-limiting embodiments of thepresent invention will become apparent to those skilled in the art uponreview of the following description of specific non-limiting embodimentsof the invention in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

For the purpose of illustrating the invention, the drawings show aspectsof one or more embodiments of the invention. However, it should beunderstood that the present invention is not limited to the precisearrangements and instrumentalities shown in the drawings, wherein:

FIG. 1 is a diagrammatic representation of an exemplary embodiment of anelectric aircraft;

FIG. 2A illustrates the side and top views of an exemplary aircraftduring the flight transition.

FIG. 2B illustrates another possible side and top views of an exemplaryaircraft during the flight transition.

FIG. 3 is a diagram illustrating an embodiment of an aircraft changingfrom hovering, vertical flight to a forward thrust configuration.

FIG. 4 illustrates a block diagram of an exemplary embodiment of asystem for autonomous transition of an electric vertical takeoff andlanding (eVTOL) aircraft;

FIG. 5 is a block diagram of an exemplary embodiment of a flightcontroller;

FIG. 6 is a block diagram of an exemplary embodiment of amachine-learning module;

FIG. 7 is a block diagram of an exemplary embodiment of a method forflight control of an eVTOL aircraft; and

FIG. 8 is a block diagram of a computing system that can be used toimplement any one or more of the methodologies disclosed herein and anyone or more portions thereof.

The drawings are not necessarily to scale and may be illustrated byphantom lines, diagrammatic representations, and fragmentary views. Incertain instances, details that are not necessary for an understandingof the embodiments or that render other details difficult to perceivemay have been omitted.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, numerousspecific details are set forth to provide a thorough understanding ofthe present invention. It will be apparent, however, that the presentinvention may be practiced without these specific details. As usedherein, the word “exemplary” or “illustrative” means “serving as anexample, instance, or illustration.” Any implementation described hereinas “exemplary” or “illustrative” is not necessarily to be construed aspreferred or advantageous over other implementations. Theimplementations described below are exemplary implementations providedto enable persons skilled in the art to make or use embodiments of thedisclosure and are not intended to limit the scope of the disclosure,which is defined by the claims. For purposes of description herein, theterms “upper”, “lower”, “left”, “rear”, “right”, “front”, “vertical”,“horizontal”, “upward”, “downward”, “forward”, “backward” andderivatives thereof shall relate to the invention as oriented in FIG. 1. Furthermore, there is no intention to be bound by any expressed orimplied theory presented in the preceding technical field, background,brief summary or the following detailed description. It is also to beunderstood that the specific devices and processes illustrated in theattached drawings, and described in the following specification, aresimply exemplary embodiments of the inventive concepts defined in theappended claims. Hence, specific dimensions and other physicalcharacteristics relating to the embodiments disclosed herein are not tobe considered as limiting, unless the claims expressly state otherwise.

At a high level, aspects of the present disclosure are directed tosystems and methods for flight control. In an embodiment, systems andmethods are provided for flight control of an electric vertical takeoffand landing (eVTOL) aircraft. Aspects of the present disclosure can beused to provide an autonomous transition between vertical lift flightand fixed wing flight of an eVTOL aircraft. Aspects of the presentdisclosure can also be used to make this transition after takeoff andinitial ascent, and before final descent and landing. This is so, atleast in part, because an aircraft flight controller is configured totranslate a preplanned trajectory to appropriate torque generation in anaircraft's plurality of propulsors. Aspects of the present disclosureadvantageously allow for a smooth and safe autonomous transition betweenvertical lift flight and fixed wing flight. Exemplary embodimentsillustrating aspects of the present disclosure are described below inthe context of several specific examples.

Referring now to FIG. 1 , an exemplary side and top view of theembodiment of aircraft 100 including a system for flight control isillustrated. In an embodiment, aircraft 100 is an electric aircraft. Inthis disclosure, “electric aircraft” is any aircraft powered byelectricity. Aircraft 100 may also be a vertical takeoff and landing(eVTOL) aircraft. As used in this disclosure an “aircraft” is anyvehicle that may fly by gaining support from the air. As a non-limitingexample, aircraft may include airplanes, helicopters, commercial and/orrecreational aircrafts, instrument flight aircrafts, drones, electricaircrafts, airliners, rotorcrafts, vertical takeoff and landingaircrafts, jets, airships, blimps, gliders, paramotors, and the like.Aircraft 100 may include an electrically powered aircraft. Inembodiments, electrically powered aircraft may be an electric verticaltakeoff and landing (eVTOL) aircraft. Electric aircraft may be capableof rotor-based cruising flight, rotor-based takeoff, rotor-basedlanding, fixed-wing cruising flight, airplane-style takeoff,airplane-style landing, and/or any combination thereof. Electricaircraft may include one or more manned and/or unmanned aircrafts.Electric aircraft may include one or more all-electric short takeoff andlanding (eSTOL) aircrafts. For example, and without limitation, eSTOLaircrafts may accelerate the plane to a flight speed on takeoff anddecelerate plane after landing. In an embodiment, and withoutlimitation, electric aircraft may be configured with an electricpropulsion assembly. Electric propulsion assembly may include anyelectric propulsion assembly as described in U.S. Nonprovisionalapplication Ser. No. 16/703,225, filed on Dec. 4, 2019, and entitled “ANINTEGRATED ELECTRIC PROPULSION ASSEMBLY,” the entirety of which isincorporated herein by reference.

Still referring to FIG. 1 , aircraft 100, may include a fuselage 104, aflight component 108 (or one or more flight components 108), and/or aflight controller 112. In one embodiment, flight component(s) 108, aplurality of laterally extending elements 116, and a plurality ofpropulsors 120. Aircraft 100 may also include pilot override switch.

As used in this disclosure, a vertical take-off and landing (VTOL)aircraft is an aircraft that can hover, take off, and land vertically.An eVTOL, as used in this disclosure, is an electrically poweredaircraft typically using an energy source, of a plurality of energysources to power aircraft. To optimize the power and energy necessary topropel aircraft 100, eVTOL may be capable of rotor-based cruisingflight, rotor-based takeoff, rotor-based landing, fixed-wing cruisingflight, airplane-style takeoff, airplane style landing, and/or anycombination thereof. Rotor-based flight, as described herein, is whereaircraft generates lift and propulsion by way of one or more poweredrotors or blades coupled with an engine, such as a “quad copter,”multi-rotor helicopter, or other vehicle that maintains its liftprimarily using downward thrusting propulsors. “Fixed-wing flight”, asdescribed herein, is where aircraft is capable of flight using wingsand/or foils that generate lift caused by aircraft's forward airspeedand the shape of the wings and/or foils, such as airplane-style flight.

Still referring to FIG. 1 , as used in this disclosure a “fuselage” is amain body of an aircraft, or in other words, the entirety of theaircraft except for a cockpit, nose, wings, empennage, nacelles, any andall control surfaces, and generally contains an aircraft's payload.Fuselage 104 may include structural elements that physically support ashape and structure of an aircraft. Structural elements may take aplurality of forms, alone or in combination with other types. Structuralelements may vary depending on a construction type of aircraft such aswithout limitation a fuselage 104. Fuselage 104 may comprise a trussstructure. A truss structure may be used with a lightweight aircraft andcomprises welded steel tube trusses. A “truss,” as used in thisdisclosure, is an assembly of beams that create a rigid structure, oftenin combinations of triangles to create three-dimensional shapes. A trussstructure may alternatively comprise wood construction in place of steeltubes, or a combination thereof. In embodiments, structural elements maycomprise steel tubes and/or wood beams. In an embodiment, and withoutlimitation, structural elements may include an aircraft skin. Aircraftskin may be layered over the body shape constructed by trusses. Aircraftskin may comprise a plurality of materials such as plywood sheets,aluminum, fiberglass, and/or carbon fiber, the latter of which will beaddressed in greater detail later herein.

In embodiments, and with continued reference to FIG. 1 , aircraftfuselage 104 may include and/or be constructed using geodesicconstruction. Geodesic structural elements may include stringers woundabout formers (which may be alternatively called station frames) inopposing spiral directions. A “stringer,” as used in this disclosure, isa general structural element that may include a long, thin, and rigidstrip of metal or wood that is mechanically coupled to and spans adistance from, station frame to station frame to create an internalskeleton on which to mechanically couple aircraft skin. A former (orstation frame) may include a rigid structural element that is disposedalong a length of an interior of aircraft fuselage 104 orthogonal to alongitudinal (nose to tail) axis of aircraft 100 and may form a generalshape of fuselage 104. A former may include differing cross-sectionalshapes at differing locations along fuselage 104, as the former is thestructural element that informs the overall shape of a fuselage 104curvature. In embodiments, aircraft skin may be anchored to formers andstrings such that the outer mold line of a volume encapsulated byformers and stringers comprises the same shape as aircraft 100 wheninstalled. In other words, former(s) may form a fuselage's ribs, and thestringers may form the interstitials between such ribs. The spiralorientation of stringers about formers may provide uniform robustness atany point on an aircraft fuselage such that if a portion sustainsdamage, another portion may remain largely unaffected. Aircraft skin maybe attached to underlying stringers and formers and may interact with afluid, such as air, to generate lift and perform maneuvers.

In an embodiment, and still referring to FIG. 1 , fuselage 104 mayinclude and/or be constructed using monocoque construction. Monocoqueconstruction may include a primary structure that forms a shell (or skinin an aircraft's case) and supports physical loads. Monocoque fuselagesare fuselages in which the aircraft skin or shell is also the primarystructure. In monocoque construction aircraft skin would support tensileand compressive loads within itself and true monocoque aircraft can befurther characterized by the absence of internal structural elements.Aircraft skin in this construction method is rigid and can sustain itsshape with no structural assistance form underlying skeleton-likeelements. Monocoque fuselage may comprise aircraft skin made fromplywood layered in varying grain directions, epoxy-impregnatedfiberglass, carbon fiber, or any combination thereof.

According to embodiments, and further referring to FIG. 1 , fuselage 104may include a semi-monocoque construction. Semi-monocoque construction,as used herein, is a partial monocoque construction, wherein a monocoqueconstruction is describe above detail. In semi-monocoque construction,aircraft fuselage 104 may derive some structural support from stressedaircraft skin and some structural support from underlying framestructure made of structural elements. Formers or station frames can beseen running transverse to the long axis of fuselage 104 with circularcutouts which are generally used in real-world manufacturing for weightsavings and for the routing of electrical harnesses and other modernon-board systems. In a semi-monocoque construction, stringers are thin,long strips of material that run parallel to fuselage's long axis.Stringers may be mechanically coupled to formers permanently, such aswith rivets. Aircraft skin may be mechanically coupled to stringers andformers permanently, such as by rivets as well. A person of ordinaryskill in the art will appreciate, upon reviewing the entirety of thisdisclosure, that there are numerous methods for mechanical fastening ofcomponents like screws, nails, dowels, pins, anchors, adhesives likeglue or epoxy, or bolts and nuts, to name a few. A subset of fuselageunder the umbrella of semi-monocoque construction includes unibodyvehicles. Unibody, which is short for “unitized body” or alternatively“unitary construction”, vehicles are characterized by a construction inwhich the body, floor plan, and chassis form a single structure. In theaircraft world, unibody may be characterized by internal structuralelements like formers and stringers being constructed in one piece,integral to the aircraft skin as well as any floor construction like adeck.

Still referring to FIG. 1 , stringers and formers, which may account forthe bulk of an aircraft structure excluding monocoque construction, maybe arranged in a plurality of orientations depending on aircraftoperation and materials. Stringers may be arranged to carry axial(tensile or compressive), shear, bending or torsion forces throughouttheir overall structure. Due to their coupling to aircraft skin,aerodynamic forces exerted on aircraft skin will be transferred tostringers. A location of said stringers greatly informs the type offorces and loads applied to each and every stringer, all of which may behandled by material selection, cross-sectional area, and mechanicalcoupling methods of each member. A similar assessment may be made forformers. In general, formers may be significantly larger incross-sectional area and thickness, depending on location, thanstringers. Both stringers and formers may comprise aluminum, aluminumalloys, graphite epoxy composite, steel alloys, titanium, or anundisclosed material alone or in combination.

In an embodiment, and still referring to FIG. 1 , stressed skin, whenused in semi-monocoque construction is the concept where the skin of anaircraft bears partial, yet significant, load in an overall structuralhierarchy. In other words, an internal structure, whether it be a frameof welded tubes, formers and stringers, or some combination, may not besufficiently strong enough by design to bear all loads. The concept ofstressed skin may be applied in monocoque and semi-monocoqueconstruction methods of fuselage 104. Monocoque comprises onlystructural skin, and in that sense, aircraft skin undergoes stress byapplied aerodynamic fluids imparted by the fluid. Stress as used incontinuum mechanics may be described in pound-force per square inch(lbf/in²) or Pascals (Pa). In semi-monocoque construction stressed skinmay bear part of aerodynamic loads and additionally may impart force onan underlying structure of stringers and formers.

Still referring to FIG. 1 , it should be noted that an illustrativeembodiment is presented only, and this disclosure in no way limits theform or construction method of a system and method for loading payloadinto an eVTOL aircraft. In embodiments, fuselage 104 may be configurablebased on the needs of the eVTOL per specific mission or objective. Thegeneral arrangement of components, structural elements, and hardwareassociated with storing and/or moving a payload may be added or removedfrom fuselage 104 as needed, whether it is stowed manually, automatedly,or removed by personnel altogether. Fuselage 104 may be configurable fora plurality of storage options. Bulkheads and dividers may be installedand uninstalled as needed, as well as longitudinal dividers wherenecessary. Bulkheads and dividers may be installed using integratedslots and hooks, tabs, boss and channel, or hardware like bolts, nuts,screws, nails, clips, pins, and/or dowels, to name a few. Fuselage 104may also be configurable to accept certain specific cargo containers, ora receptable that can, in turn, accept certain cargo containers.

Still referring to FIG. 1 , aircraft 100 may include a plurality oflaterally extending elements attached to fuselage 104. As used in thisdisclosure a “laterally extending element” is an element that projectsessentially horizontally from fuselage, including an outrigger, a rotor,a spar, and/or a fixed wing that extends from fuselage. Wings may bestructures which may include airfoils configured to create a pressuredifferential resulting in lift. Wings may generally dispose on the leftand right sides of the aircraft symmetrically, at a point between noseand empennage. Wings may comprise a plurality of geometries in planformview, swept swing, tapered, variable wing, triangular, oblong,elliptical, square, among others. A wing's cross section geometry maycomprise an airfoil. An “airfoil” as used in this disclosure is a shapespecifically designed such that a fluid flowing above and below it exertdiffering levels of pressure against the top and bottom surface. Inembodiments, the bottom surface of an aircraft can be configured togenerate a greater pressure than does the top, resulting in lift.Laterally extending element may comprise differing and/or similarcross-sectional geometries over its cord length or the length from wingtip to where wing meets the aircraft's body. One or more wings may besymmetrical about the aircraft's longitudinal plane, which comprises thelongitudinal or roll axis reaching down the center of the aircraftthrough the nose and empennage, and plane's yaw axis. Laterallyextending element may include control surfaces configured to becommanded by a pilot or pilots to change a wing's geometry and thereforeits interaction with a fluid medium, like air. Control surfaces maycomprise flaps, ailerons, tabs, spoilers, and slats, among others. Thecontrol surfaces may dispose on the wings in a plurality of locationsand arrangements and in embodiments may be disposed at the leading andtrailing edges of the wings, and may be configured to deflect up, down,forward, aft, or a combination thereof. An aircraft, including adual-mode aircraft may comprise a combination of control surfaces toperform maneuvers while flying or on ground.

Still referring to FIG. 1 , aircraft 100 may include a plurality offlight components 108. As used in this disclosure a “flight component”is a component that promotes flight and guidance of an aircraft. In anembodiment, flight component 108 may be mechanically coupled to anaircraft. As used herein, a person of ordinary skill in the art wouldunderstand “mechanically coupled” to mean that at least a portion of adevice, component, or circuit is connected to at least a portion of theaircraft via a mechanical coupling. Said mechanical coupling mayinclude, for example, rigid coupling, such as beam coupling, bellowscoupling, bushed pin coupling, constant velocity, split-muff coupling,diaphragm coupling, disc coupling, donut coupling, elastic coupling,flexible coupling, fluid coupling, gear coupling, grid coupling, hirthjoints, hydrodynamic coupling, jaw coupling, magnetic coupling, Oldhamcoupling, sleeve coupling, tapered shaft lock, twin spring coupling, ragjoint coupling, universal joints, or any combination thereof. In anembodiment, mechanical coupling may be used to connect the ends ofadjacent parts and/or objects of an electric aircraft. Further, in anembodiment, mechanical coupling may be used to join two pieces ofrotating electric aircraft components.

Still referring to FIG. 1 , in an embodiment, plurality of flightcomponents 108 of aircraft 100 may include at least a plurality ofpropulsors 120, each of which is configured to rotate between a verticallift position utilizing lift, or hover, flight components and a forwardthrust position utilizing thrust flight components. Vertical liftposition may be recognized when plurality of laterally extendingelements are in a horizontal, zero degree angle and plurality ofpropulsors are facing directly upward, as seen in system 204, which isfurther described below with reference to FIG. 2 . Forward thrustposition may be recognized when plurality of laterally extendingelements have rotated 90 degrees counterclockwise and now sit at aperfect vertical while plurality of propulsors are now facing sideways,as seen in system 208, which is further described below with referenceto FIG. 2 . As used in this disclosure a “thrust flight component” is aflight component that is mounted such that the component thrusts theflight component through a medium. As a non-limiting example, thrustflight component may include a pusher flight component such as a pusherpropeller, a pusher motor, a pusher propulsor, and the like.Additionally, or alternatively, pusher flight component may include aplurality of pusher flight components. As a further non-limitingexample, thrust flight component may include a puller flight componentsuch as a puller propeller, a puller motor, a puller propulsor, and thelike. Additionally, or alternatively, puller flight component mayinclude a plurality of puller flight components. As used in thisdisclosure a “lift component” is a component and/or device used topropel a craft upward by exerting downward force on a fluid medium,which may include a gaseous medium such as air or a liquid medium suchas water. Lift component 112 may include any device or component thatconsumes electrical power on demand to propel an electric aircraft in adirection or other vehicle while on ground or in-flight. For example,and without limitation, lift component 112 may include a rotor,propeller, paddle wheel and the like thereof, wherein a rotor is acomponent that produces torque along a longitudinal axis, and apropeller produces torquer along a vertical axis. In an embodiment, liftcomponent 112 may include a propulsor. In an embodiment, when apropulsor twists and pulls air behind it, it will, at the same time,push an aircraft forward with an equal amount of force. As a furthernon-limiting example, lift component 112 may include a thrust elementwhich may be integrated into the propulsor. The thrust element mayinclude, without limitation, a device using moving or rotating foils,such as one or more rotors, an airscrew or propeller, a set of airscrewsor propellers such as contra-rotating propellers, a moving or flappingwing, or the like. Further, a thrust element, for example, can includewithout limitation a marine propeller or screw, an impeller, a turbine,a pump-jet, a paddle or paddle-based device, or the like. The more airpulled behind an aircraft, the greater the force with which the aircraftis pushed forward.

With continued reference to FIG. 1 , in an embodiment, aircraft 100 mayinclude a flight controller 112. Flight controller 112 may beimplemented, without limitation, as described in further details below.In embodiments, flight controller 112 may be installed in an aircraft,may control aircraft remotely, and/or may include an element installedin aircraft and a remote element in communication therewith. Flightcontroller 112, in an embodiment, is located within fuselage 104 of theaircraft. In accordance with some embodiments, flight controller isconfigured to operate a vertical lift flight (upwards or downwards, thatis, takeoff or landing), a transition between a vertical lift flight andhorizontal flight, and horizontal flight.

Still referring to FIG. 1 , in an embodiment, and without limitation,flight controller 112 may be configured to operate aircraft according toa fixed-wing flight capability. A “fixed-wing flight capability,” asused in this disclosure, is a method of flight wherein plurality oflaterally extending elements generate lift. For example, and withoutlimitation, fixed-wing flight capability may generate lift as a functionof an airspeed of aircraft 100 and one or more airfoil shapes oflaterally extending elements, wherein an airfoil is described above indetail. As a further non-limiting example, flight controller 112 mayoperate fixed-wing flight capability as a function of reducing appliedtorque on plurality of propulsors 120. For example, and withoutlimitation, flight controller 112 may reduce a torque of 9 Nm applied toa first set of propulsors to a torque of 2 Nm. As a further non-limitingexample, flight controller 112 may reduce a torque of 12 Nm applied to afirst set of propulsors to a torque of 0 Nm. In an embodiment, andwithout limitation, flight controller 112 may produce fixed-wing flightcapability as a function of increasing forward thrust exerted by therotation of propulsors. For example, and without limitation, flightcontroller 112 may increase a forward thrust of 100 kN produced by therotation of propulsors to a forward thrust of 569 kN. In an embodiment,and without limitation, an amount of lift generation may be related toan amount of forward thrust generated to increase airspeed velocity,wherein the amount of lift generation may be directly proportional tothe amount of forward thrust produced. Additionally or alternatively,flight controller may include an inertia compensator. As used in thisdisclosure an “inertia compensator” is one or more computing devices,electrical components, logic circuits, processors, and the like there ofthat are configured to compensate for inertia in one or more liftpropulsor components present in aircraft 100. Inertia compensator mayalternatively or additionally include any computing device used as aninertia compensator as described in U.S. Nonprovisional application Ser.No. 17/106,557, filed on Nov. 30, 2020, and entitled “SYSTEM AND METHODFOR FLIGHT CONTROL IN ELECTRIC AIRCRAFT,” the entirety of which isincorporated herein by reference.

In an embodiment, and still referring to FIG. 1 , flight controller 112may be configured to perform a reverse thrust command. As used in thisdisclosure a “reverse thrust command” is a command to perform a thrustthat forces a medium towards the relative air opposing aircraft 100. Forexample, reverse thrust command may include a thrust of 180 N directedtowards the nose of aircraft to at least repel and/or oppose therelative air. Reverse thrust command may alternatively or additionallyinclude any reverse thrust command as described in U.S. Nonprovisionalapplication Ser. No. 17/319,155, filed on May 13, 2021, and entitled“AIRCRAFT HAVING REVERSE THRUST CAPABILITIES,” the entirety of which isincorporated herein by reference. In another embodiment, flightcontroller may be configured to perform a regenerative drag operation.As used in this disclosure a “regenerative drag operation” is anoperating condition of an aircraft, wherein aircraft has a negativethrust and/or is reducing in airspeed velocity. For example, and withoutlimitation, regenerative drag operation may include a positive propellerspeed and a negative propeller thrust. Regenerative drag operation mayalternatively or additionally include any regenerative drag operation asdescribed in U.S. Nonprovisional application Ser. No. 17/319,155.

Referring now to FIG. 2A, side views 204 and 208 of aircraft 100 at bothhorizontal and vertical flight and top view 212 of aircraft 100 isillustrated. System 200 may include a fuselage 104, a plurality oflaterally extending elements 116, a plurality of propulsors 120, and aflight controller 112. “Plurality of propulsors” may be defined as anytype of mechanical device that produces a propulsive force in a specificdirection. Propulsors may include fixed pitch propeller, constant speedpropellor, ground adjustable propeller, or any versions thereof.Plurality of propulsors can move independently of the wing, such thatthe wing remains in the same position during the transition. The pointat which the aircraft begins to change from vertical to horizontalflight is the “flight transition point”.

Still referencing FIG. 2A, diagrams 204 and 208 illustrate exemplaryembodiments, respectively, of propulsors 120 in lift position 204 andforward thrust position 208. To hover or enact vertical flight mode,plurality of propulsors 120 may act as lift propulsors and sit atzero-degree angles on an axis of rotation, for instance and withoutlimitation as seen in diagram 204. To fly horizontally, plurality ofpropulsors 120 may act as pusher propulsors and may shift to a positionin which an axis of rotation of propulsor blades is closer to horizontalthan in the lift position, for instance and without limitation resultingin a position as illustrated in in diagram 208. In diagram 212, the topview of aircraft 100 and plurality of propulsors 120 is shown.

Still referring to FIG. 2A, plurality of laterally extending elements116 and plurality of propulsors 120 are attached to fuselage 104 byrotating component 216. Rotating component 216 permits fuselage 104 andlaterally extending elements 116 to rotate with respect to each other onan axis of rotation. Axis of rotation is the axis of the fuselage whichis an invisible line running from wing end to wing end that thecomponents revolve around. Plurality of propulsors 120 rotate along withplurality of laterally extending elements since they are rigidlyattached. Rotating component 216 may include any and all types of rotaryactuators, bearings, and other types of machinery components that allowrotation. “Rotational actuator” may include any component of a machinethat is responsible for the rotational movement of a system. Types ofactuators may include hydraulic actuators, pneumatic actuators, electricactuators, thermal actuators, and mechanical actuators. “Bearing” may bedefined as any component that supports, or is supported by, anothercomponent. Types of bearings may include aircraft track rollers, airframe control bearings, spherical bearings, rod end bearings, instrumentbearings, thrust bearings, sleeve bearings, and the like. Rotatingcomponent 216 may consists of any machinery that will allow rotation ofplurality of laterally extending elements 116 and plurality ofpropulsors 120. Rotating component 216 may also include a damper. Adamper in rotational component 216 may prevent fast or excessiveswinging of laterally extending elements 116.

Referring now to FIG. 2B, another exemplary system 200 is shown. Sideviews 220 and 224 of aircraft 100 at both horizontal and vertical flightand top view 228 of aircraft 100 are illustrated. System 200 may includea fuselage 104, a plurality of laterally extending elements 116, a firstpropulsor 232, a second propulsor 236, a flight controller 112, and arotating component 240. A “first propulsor” is the propulsor closest tothe nose of the aircraft and is configured to rotate. A “secondpropulsor” is the propulsor closest to the back of the aircraft and isrigidly attached to the wing, and therefore is not configured to rotate.Propulsors may include fixed pitch propeller, constant speed propellor,ground adjustable propeller, or any versions thereof.

Still referencing FIG. 2B, diagrams 220 and 224 illustrate exemplaryembodiments, respectively, of propulsors 232 and 236 in lift position220 and forward thrust position 224. For the second propulsor 236, thelift position and forward thrust position are the same since thecomponent does not rotate in this embodiment. To hover or enact verticalflight mode, first propulsor 232 may act as a lift propulsor and sit atzero-degree angles on an axis of rotation, for instance and withoutlimitation as seen in diagram 220. To fly horizontally, first propulsor232 may act as a pusher propulsor and may shift to a position in whichan axis of rotation of propulsor blades is closer to horizontal than inthe lift position, for instance and without limitation resulting in aposition as illustrated in in diagram 224. In diagram 228, the top viewof aircraft 100 and plurality of first propulsors 232 and secondpropulsors 236 are shown.

Still referring to FIG. 2B, plurality of laterally extending elements116, and first propulsors 232 are attached to fuselage 104 by rotatingcomponent 240, while second propulsors 236 are rigidly attached to thewings. In this embodiment, propulsors can operate independently suchthat they do not need to perform the same rotation at the same time andcan be controlled independently. Rotating component 240 permits fuselage104 and laterally extending elements 116 to rotate with respect to eachother on an axis of rotation. First propulsors 232 rotate along withplurality of laterally extending elements since they are rigidlyattached. Rotating component 240 may include any and all types of rotaryactuators, bearings, and other types of machinery components that allowrotation. “Rotational actuator” may include any component of a machinethat is responsible for the rotational movement of a system. Types ofactuators may include hydraulic actuators, pneumatic actuators, electricactuators, thermal actuators, and mechanical actuators. “Bearing” may bedefined as any component that supports, or is supported by, anothercomponent. Types of bearings may include aircraft track rollers, airframe control bearings, spherical bearings, rod end bearings, instrumentbearings, thrust bearings, sleeve bearings, and the like. Rotatingcomponent 240 may consists of any machinery that will allow rotation ofplurality of laterally extending elements 116 and first propulsors 232.Rotating component 240 may also include a damper. A damper in rotationalcomponent 240 may prevent fast or excessive swinging of laterallyextending elements 116.

Referring now to FIG. 3 , a schematic diagram of exemplary embodimentsof simplified flight paths for an eVTOL aircraft during vertical andhorizontal flight is shown. The aircraft can be any of the aircraftsdiscussed herein with reference to FIGS. 1 and 2 . During aircraftflight, a vertical lift flight path (upward) is followed by a transitionflight path 304 which is then followed by a fixed wing flight path. Thisexecution of a desired flight trajectory is accomplished by anautonomous transition between vertical lift flight and fixed wingflight. Flight trajectory may be stored in the memory of flightcontroller 112, refer to further disclosure for details. In anembodiment, a flight controller is configured to translate a preplannedtrajectory to appropriate torque generation in plurality of laterallyextending elements 116 and plurality of propulsors 120, as described ingreater detail above and later herein. FIG. 3 continues the example ofFIG. 2 and shows the same aircraft 100 along with the proper rotationangles of the laterally extending elements 116 and propulsors 120.

Referring now to FIG. 4 , an exemplary embodiment of a system 400 forautonomous transition of an electric vertical takeoff and landing(eVTOL) aircraft, such as without limitation an aircraft 100 of FIG. 1 ,is illustrated. System 400 may include a fuselage 104, a plurality oflaterally extending elements 116, a plurality of propulsors 120, and aflight controller 112.

Still referring to FIG. 4 , plurality of propulsors may be configured togenerate a generally upward thrust for eVTOL aircraft when at azero-degree angle. Plurality of propulsors may be configured to generatea generally forward thrust for the eVTOL aircraft when rotated 90degrees counterclockwise. Flight controller 112 may include a computingdevice. Flight controller may include a proportional-integral-derivative(PID) controller. Flight controller may be configured to increase anddecrease rotational speed of laterally extending elements 116 andpropulsors 120.

Still referring to FIG. 4 , in an embodiment, and without limitation,the more air forced behind aircraft, the greater thrust force with whichthe aircraft is pushed horizontally will be. In another embodiment, andwithout limitation, forward thrust may force aircraft 100 through themedium of relative air. Additionally or alternatively, plurality offlight components 108 may include one or more puller components. As usedin this disclosure a “puller component” is a component that pulls and/ortows an aircraft through a medium. As a non-limiting example, pullercomponent may include a flight component such as a puller propeller, apuller motor, a tractor propeller, a puller propulsor, and the like.Additionally, or alternatively, puller component may include a pluralityof puller flight components.

Still referring to FIG. 4 , in an embodiment, plurality of propulsors120 may include a plurality of blades. As used in this disclosure a“blade” is a propeller that converts rotary motion from an engine orother power source into a swirling slipstream. In an embodiment, blademay convert rotary motion to push propeller forwards or backwards. In anembodiment plurality of propulsors 120 may include a rotatingpower-driven hub, to which are attached several radial airfoil-sectionblades such that the whole assembly rotates about a longitudinal axis.Blades may be configured at an angle of attack, wherein an angle ofattack is described in detail below. In an embodiment, and withoutlimitation, angle of attack may include a fixed angle of attack. As usedin this disclosure a “fixed angle of attack” is fixed angle between achord line of a blade and relative wind. As used in this disclosure a“fixed angle” is an angle that is secured and/or unmovable from theattachment point and is achieved through rotation of the actuatorattached to the fuselage. For example, and without limitation fixedangle of attack may be 3.2° as a function of a pitch angle of 9.7° and arelative wind angle 6.5°. In another embodiment, and without limitation,angle of attack may include a variable angle of attack. As used in thisdisclosure a “variable angle of attack” is a variable and/or moveableangle between a chord line of a blade and relative wind. As used in thisdisclosure a “variable angle” is an angle that is moveable from anattachment point. For example, and without limitation variable angle ofattack may be a first angle of 4.7° as a function of a pitch angle of7.1° and a relative wind angle 2.4°, wherein the angle adjusts and/orshifts to a second angle of 2.7° as a function of a pitch angle of 5.1°and a relative wind angle 2.4°. In an embodiment, angle of attack beconfigured to produce a fixed pitch angle. As used in this disclosure a“fixed pitch angle” is a fixed angle between a cord line of a blade androtational velocity direction. For example, and without limitation,fixed pitch angle may include 18°. In another embodiment fixed angle ofattack may be manually variable to a few set positions to adjust one ormore lifts of aircraft prior to flight. In an embodiment, blades for anaircraft are designed to be fixed to their hub at an angle similar tothe thread on a screw makes an angle to the shaft; this angle may bereferred to as a pitch or pitch angle which will determine a speed offorward movement as the blade rotates.

In an embodiment, and still referring to FIG. 4 , plurality ofpropulsors 120 may be configured to produce a lift. As used in thisdisclosure a “lift” is a perpendicular force to the oncoming flowdirection of fluid surrounding the surface. For example, and withoutlimitation relative air speed may be horizontal to aircraft, whereinlift force may be a force exerted in a vertical direction, directingaircraft upwards. In an embodiment, and without limitation, plurality ofpropulsors 120 may produce lift as a function of applying a torque tolift component. As used in this disclosure a “torque” is a measure offorce that causes an object to rotate about an axis in a direction. Forexample, and without limitation, torque may rotate an aileron and/orrudder to generate a force that may adjust and/or affect altitude,airspeed velocity, groundspeed velocity, direction during flight, and/orthrust. For example, one or more flight components 108, as described inFIG. 1 , such as a power sources may apply a torque on plurality ofpropulsors 120 to produce lift. As used in this disclosure a “powersource” is a source that that drives and/or controls any other flightcomponent. For example, and without limitation power source may includea motor that operates to move one or more lift propulsor components, todrive one or more blades, or the like thereof. A motor may be driven bydirect current (DC) electric power and may include, without limitation,brushless DC electric motors, switched reluctance motors, inductionmotors, or any combination thereof. A motor may also include electronicspeed controllers or other components for regulating motor speed,rotation direction, and/or dynamic braking.

Still referring to FIG. 4 , system 400 may include a pilot overrideswitch 124. Pilot override switch 124 may be attached to eVTOL aircraft.Pilot override switch 124 may be configured to alter control of aircraft100 from autonomous to non-autonomous flight modes. As used in thisdisclosure, “autonomous” means that aircraft 100 is set to self-governits own flight path and does not need a pilot to oversee flightcontrols. “Non-autonomous” describes a mode of flight where a pilot isneeded to control flight components.

Still referring to FIG. 4 , as used in this disclosure, a “pilotoverride switch” is a mechanism or means which allows a pilot to takecontrol of flight components (for example, and without limitation,pusher component and lift component) of an aircraft. For example, andwithout limitation, pilot override switch 124 may include push buttons,lever, switch, and other binary inputs. Pilot override switch 124 isconfigured to translate a pilot's desire to take back control of eachflight component of plurality of flight components 108. Pilot overrideswitch 124 is configured to regain control of autonomous aircraft 100and its flight component(s) 108.

Still referring to FIG. 4 , aircraft and/or flight controller may beconfigured to transition from vertical lift flight to fixed wing flight.As used in this disclosure, “vertical lift flight” refers to thesubstantially vertical, upward, or downward, flight of aircraft. As usedin this disclosure, “fixed wing flight” refers to the substantiallyhorizontal, forward, or backward, flight of aircraft. “Transition”, asused in this disclosure, refers to the transition of aircraft'strajectory between vertical lift flight and fixed wing flight.Transition from vertical lift flight to fixed wing flight may occur ator after a moment when aircraft's speed is such as to avoid stall; thatis, aircraft's speed maybe at least at or above, a stall speed. As usedin this disclosure, “stall speed” is a metric that refers to the minimumspeed for an aircraft to produce lift. For example, when airplanes flyslower than their respective stall speed, they may be unable to producelift. Once the desire flight angle is reached, rotational componentstops movement. In this disclosure, “desire flight angle” is the angleof flight the pilot is trying to reach by rotating the extendingelements and propulsors.

Still referring to FIG. 4 , aircraft and/or system 400 may include apower source. Power source may include an energy source. An energysource may include, for example, an electrical energy source agenerator, a photovoltaic device, a fuel cell such as a hydrogen fuelcell, direct methanol fuel cell, and/or solid oxide fuel cell, anelectric energy storage device (e.g., a capacitor, an inductor, and/or abattery). An electrical energy source may also include a battery cell,or a plurality of battery cells connected in series into a module andeach module connected in series or in parallel with other modules.Configuration of an energy source containing connected modules may bedesigned to meet an energy or power requirement and may be designed tofit within a designated footprint in an electric aircraft in whichaircraft 100 may be incorporated.

In an embodiment, and still referring to FIG. 4 , an energy source maybe used to provide a steady supply of electrical power to a load overthe course of a flight by a vehicle or other electric aircraft. Forexample, an energy source may be capable of providing sufficient powerfor “cruising” and other relatively low-energy phases of flight. Anenergy source may also be capable of providing electrical power for somehigher-power phases of flight as well, particularly when the energysource is at a high SOC, as may be the case for instance during takeoff.In an embodiment, an energy source may be capable of providingsufficient electrical power for auxiliary loads including withoutlimitation, lighting, navigation, communications, de-icing, steering, orother systems requiring power or energy. Further, an energy source maybe capable of providing sufficient power for controlled descent andlanding protocols, including, without limitation, hovering descent, orrunway landing. As used herein an energy source may have high powerdensity where electrical power an energy source can usefully produce perunit of volume and/or mass is relatively high. “Electrical power,” asused in this disclosure, is defined as a rate of electrical energy perunit time. An energy source may include a device for which power thatmay be produced per unit of volume and/or mass has been optimized, atthe expense of maximal total specific energy density or power capacity,during design. Non-limiting examples of items that may be used as atleast an energy source may include batteries used for startingapplications including Li ion batteries which may include NCA, NMC,Lithium iron phosphate (LiFePO4) and Lithium Manganese Oxide (LMO)batteries, which may be mixed with another cathode chemistry to providemore specific power if the application requires Li metal batteries,which have a lithium metal anode that provides high power on demand, Liion batteries that have a silicon or titanite anode, energy source maybe used, in an embodiment, to provide electrical power to an electricaircraft or drone, such as an electric aircraft vehicle, during momentsrequiring high rates of power output, including without limitationtakeoff, landing, thermal de-icing and situations requiring greaterpower output for reasons of stability, such as high turbulencesituations, as described in further detail below. A battery may include,without limitation a battery using nickel based chemistries such asnickel cadmium or nickel metal hydride, a battery using lithium ionbattery chemistries such as a nickel cobalt aluminum (NCA), nickelmanganese cobalt (NMC), lithium iron phosphate (LiFePO4), lithium cobaltoxide (LCO), and/or lithium manganese oxide (LMO), a battery usinglithium polymer technology, lead-based batteries such as withoutlimitation lead acid batteries, metal-air batteries, or any othersuitable battery. Persons skilled in the art, upon reviewing theentirety of this disclosure, will be aware of various devices ofcomponents that may be used as an energy source.

Still referring to FIG. 4 , an energy source may include a plurality ofenergy sources, referred to herein as a module of energy sources. Amodule may include batteries connected in parallel or in series or aplurality of modules connected either in series or in parallel designedto deliver both the power and energy requirements of the application.Connecting batteries in series may increase the voltage of at least anenergy source which may provide more power on demand. High voltagebatteries may require cell matching when high peak load is needed. Asmore cells are connected in strings, there may exist the possibility ofone cell failing which may increase resistance in the module and reducean overall power output as a voltage of the module may decrease becauseof that failing cell. Connecting batteries in parallel may increasetotal current capacity by decreasing total resistance, and it also mayincrease overall amp-hour capacity. Overall energy and power outputs ofat least an energy source may be based on individual battery cellperformance or an extrapolation based on measurement of at least anelectrical parameter. In an embodiment where an energy source mayinclude a plurality of battery cells, overall power output capacity maybe dependent on electrical parameters of each individual cell. If onecell experiences high self-discharge during demand, power drawn from atleast an energy source may be decreased to avoid damage to the weakestcell. An energy source may further include, without limitation, wiring,conduit, housing, cooling system and battery management system. Personsskilled in the art will be aware, after reviewing the entirety of thisdisclosure, of many different components of an energy source.

In an embodiment and still referring to FIG. 4 , a plurality ofpropulsors may be arranged in a quad copter orientation. Quad copterorientation can be seen in FIG. 2 . As used in this disclosure a “quadcopter orientation” is at least a lift component oriented in a geometricshape and/or pattern, wherein each of the lift components is locatedalong a vertex of the geometric shape. For example, and withoutlimitation, a square quad copter orientation may have four liftpropulsor components oriented in the geometric shape of a square,wherein four lift propulsor components are located along four verticesof the square shape. As a further non-limiting example, a hexagonal quadcopter orientation may have six lift components oriented in thegeometric shape of a hexagon, wherein six lift components are locatedalong six vertices of the hexagon shape. In an embodiment, and withoutlimitation, quad copter orientation may include a first set of liftcomponents and a second set of lift components, wherein first set oflift components and second set of lift components may include two liftcomponents each, wherein the first set of lift components and a secondset of lift components are distinct from one another. For example, andwithout limitation, the first set of lift components may include twolift components that rotate in a clockwise direction, wherein the secondset of lift propulsor components may include two lift components thatrotate in a counterclockwise direction. In an embodiment, and withoutlimitation, the first set of lift components may be oriented along aline oriented 45° from the longitudinal axis of aircraft 100, as seen inFIG. 1 . In another embodiment, and without limitation, the second setof lift components may be oriented along a line oriented 135° from thelongitudinal axis, wherein the first set of lift components line and thesecond set of lift components are perpendicular to each other.

Still referring to FIG. 4 , flight component(s) 108 may include any suchcomponents and related devices as disclosed in U.S. Nonprovisionalapplication Ser. No. 16/427,298, filed on May 30, 2019, entitled“SELECTIVELY DEPLOYABLE HEATED PROPULSOR SYSTEM,”, U.S. Nonprovisionalapplication Ser. No. 16/703,225, filed on Dec. 4, 2019, entitled “ANINTEGRATED ELECTRIC PROPULSION ASSEMBLY,”, U.S. Nonprovisionalapplication Ser. No. 16/910,255, filed on Jun. 24, 2020, entitled “ANINTEGRATED ELECTRIC PROPULSION ASSEMBLY,”, U.S. Nonprovisionalapplication Ser. No. 17/319,155, filed on May 13, 2021, entitled“AIRCRAFT HAVING REVERSE THRUST CAPABILITIES,”, U.S. Nonprovisionalapplication Ser. No. 16/929,206, filed on Jul. 15, 2020, entitled “AHOVER AND THRUST CONTROL ASSEMBLY FOR DUAL-MODE AIRCRAFT,”, U.S.Nonprovisional application Ser. No. 17/001,845, filed on Aug. 25, 2020,entitled “A HOVER AND THRUST CONTROL ASSEMBLY FOR DUAL-MODE AIRCRAFT,”,U.S. Nonprovisional application Ser. No. 17/186,079, filed on Feb. 26,2021, entitled “METHODS AND SYSTEM FOR ESTIMATING PERCENTAGE TORQUEPRODUCED BY A PROPULSOR CONFIGURED FOR USE IN AN ELECTRIC AIRCRAFT,”,and U.S. Nonprovisional application Ser. No. 17/321,662, filed on May17, 2021, entitled “AIRCRAFT FOR FIXED PITCH LIFT,”, the entirety ofeach one of which is incorporated herein by reference.

Still referring to FIG. 4 , system may include flight controller 112.Flight controller 112 may be communicatively connected to pilot overrideswitch 124. “Communicatively connected”, for the purposes of thisdisclosure, refers to two or more components electrically, or otherwiseconnected or coupled and configured to transmit and receive signals fromone another. Signals must include visuals and may include electrical,electromagnetic, audio, radio waves, combinations thereof, and the like,among others. Flight controller 112 may include any computing deviceand/or combination of computing devices programmed to operate aircraft,for instance and without limitation as described in further detailbelow.

Still referring to FIG. 4 , in an embodiment, flight controller 112 mayinclude a proportional-integral-derivative (PID) controller. Flightcontroller 112 is configured to initiate rotation 404 of plurality ofpropulsors and laterally extending elements which, in an embodiment,will eventually generate forward or substantially horizontal thrust oncedesired angle is reached. Flight controller 112 is configured toterminate rotation 408 of plurality of propulsors 120 and laterallyextending elements 116 (for example, by cutting power to it) oncedesired angle is reached.

With continued reference to FIG. 4 , flight controller 112 may beconfigured to detect when rotation is activated autonomously and when itis switched off. Flight controller 112 is further configured to monitorthe operations of rotation of plurality of propulsors 120 and laterallyextending elements 116. Flight controller 112, in an embodiment, may beconfigured to estimate the stall speed of aircraft. Flight controller112 may also be configured to provide stall speed data to pilot, asneeded or desired. During transition between vertical lift flight andhorizontal flight, flight controller may be configured to monitor thetrajectory followed by aircraft as controlled by the predisposedtrajectory. In embodiments in accordance with the present disclosure,the decisions to transition between vertical lift flight and fixed wingflight are preplanned. Aircraft may be equipped with visual guides forpilot. Some such suitable visual guides are described in in U.S.Nonprovisional application Ser. No. 17/362,001, filed on Jun. 29, 2021,entitled “SYSTEM FOR A GUIDANCE INTERFACE FOR A VERTICAL TAKE-OFF ANDLANDING AIRCRAFT,”, the entirety of which is incorporated herein byreference.

Still referring to FIG. 4 , in an embodiment, flight controller 112 isconfigured to monitor aircraft's flight conditions and operatingparameters to ensure that they are within acceptable limits. These mayinclude, for example and without limitation, aircraft's vertical lift,horizontal thrust, trajectory, speed, and the like, among others. Flightcontroller 112 may be configured to monitor such flight conditions andoperating parameters based on current and/or projected responses topreplanned trajectory. In an embodiment, flight controller 112 may beconfigured to warn pilot of a potentially unacceptable pilot commandand/or to override pilot's command, as needed or desired.

Still referring to FIG. 4 , in an embodiment, flight controller 112 isconfigured to automatically perform flight maneuvers. For example, andwithout limitation, flight controller is configured to automaticallytransition between vertical lift flight and fixed wing flight.

Still referring to FIG. 4 , flight controller 112 may include any of theflight controllers as disclosed in U.S. Nonprovisional application Ser.No. 16/929,206, filed on Jul. 15, 2020, entitled “A HOVER AND THRUSTCONTROL ASSEMBLY FOR DUAL-MODE AIRCRAFT,”, U.S. Nonprovisionalapplication Ser. No. 17/001,845, filed on Aug. 25, 2020, entitled “AHOVER AND THRUST CONTROL ASSEMBLY FOR DUAL-MODE AIRCRAFT,”, U.S.Nonprovisional application Ser. No. 17/321,662, filed on May 17, 2021,entitled “AIRCRAFT FOR FIXED PITCH LIFT,”, U.S. Nonprovisionalapplication Ser. No. 17/218,387, filed on Mar. 31, 2021, entitled“METHOD AND SYSTEM FOR FLY-BY-WIRE FLIGHT CONTROL CONFIGURED FOR USE INELECTRIC AIRCRAFT,”, and U.S. Nonprovisional application Ser. No.17/348,851 filed on Jun. 16, 2021, entitled “AIRCRAFT FOR VECTORING APLURALITY OF PROPULSORS,”, the entirety of each one of which isincorporated herein by reference.

As used in this disclosure, “flight path angle” is the angle betweenflight path vector of an aircraft and the horizon. Stated simply, flightpath angle can also be described as the climb or descent angle. “Pitchangle” (or pitch attitude), as used in this disclosure, is the anglebetween the longitudinal axis of an aircraft (or component thereof) andthe horizon. As used in this disclosure, “angle of attack” is anglebetween the chord of an airfoil (or component thereof) and the relativewind. In other words, it can be approximated as the difference betweenpitch angle and flight path angle.

Now referring to FIG. 5 , an exemplary embodiment 500 of a flightcontroller 112 is illustrated. As used in this disclosure a “flightcontroller” is a computing device of a plurality of computing devicesdedicated to data storage, security, distribution of traffic for loadbalancing, and flight instruction. Flight controller 112 may includeand/or communicate with any computing device as described in thisdisclosure, including without limitation a microcontroller,microprocessor, digital signal processor (DSP) and/or system on a chip(SoC) as described in this disclosure. Further, flight controller 112may include a single computing device operating independently, or mayinclude two or more computing device operating in concert, in parallel,sequentially or the like; two or more computing devices may be includedtogether in a single computing device or in two or more computingdevices. In embodiments, flight controller 112 may be installed in anaircraft, may control aircraft remotely, and/or may include an elementinstalled in the aircraft and a remote element in communicationtherewith.

In an embodiment, and still referring to FIG. 5 , flight controller 112may include a signal transformation component 504. As used in thisdisclosure a “signal transformation component” is a component thattransforms and/or converts a first signal to a second signal, wherein asignal may include one or more digital and/or analog signals. Forexample, and without limitation, signal transformation component 504 maybe configured to perform one or more operations such as preprocessing,lexical analysis, parsing, semantic analysis, and the like thereof. Inan embodiment, and without limitation, signal transformation component504 may include one or more analog-to-digital convertors that transforma first signal of an analog signal to a second signal of a digitalsignal. For example, and without limitation, an analog-to-digitalconverter may convert an analog input signal to a 10-bit binary digitalrepresentation of that signal. In another embodiment, signaltransformation component 504 may include transforming one or morelow-level languages such as, but not limited to, machine languagesand/or assembly languages. For example, and without limitation, signaltransformation component 504 may include transforming a binary languagesignal to an assembly language signal. In an embodiment, and withoutlimitation, signal transformation component 504 may include transformingone or more high-level languages and/or formal languages such as but notlimited to alphabets, strings, and/or languages. For example, andwithout limitation, high-level languages may include one or more systemlanguages, scripting languages, domain-specific languages, visuallanguages, esoteric languages, and the like thereof. As a furthernon-limiting example, high-level languages may include one or morealgebraic formula languages, business data languages, string and listlanguages, object-oriented languages, and the like thereof.

Still referring to FIG. 5 , signal transformation component 504 may beconfigured to optimize an intermediate representation 508. As used inthis disclosure an “intermediate representation” is a data structureand/or code that represents input signal. Signal transformationcomponent 504 may optimize intermediate representation as a function ofa data-flow analysis, dependence analysis, alias analysis, pointeranalysis, escape analysis, and the like thereof. In an embodiment, andwithout limitation, signal transformation component 504 may optimizeintermediate representation 508 as a function of one or more inlineexpansions, dead code eliminations, constant propagation, looptransformations, and/or automatic parallelization functions. In anotherembodiment, signal transformation component 504 may optimizeintermediate representation as a function of a machine dependentoptimization such as a peephole optimization, wherein a peepholeoptimization may rewrite short sequences of code into more efficientsequences of code. Signal transformation component 504 may optimizeintermediate representation to generate an output language, wherein an“output language,” as used herein, is the native machine language offlight controller 112. For example, and without limitation, nativemachine language may include one or more binary and/or numericallanguages.

In an embodiment, and without limitation, signal transformationcomponent 504 may include transform one or more inputs and outputs as afunction of an error correction code. An error correction code, alsoknown as error correcting code (ECC), is an encoding of a message or lotof data using redundant information, permitting recovery of corrupteddata. An ECC may include a block code, in which information is encodedon fixed-size packets and/or blocks of data elements such as symbols ofpredetermined size, bits, or the like. Reed-Solomon coding, in whichmessage symbols within a symbol set having q symbols are encoded ascoefficients of a polynomial of degree less than or equal to a naturalnumber k, over a finite field F with q elements; strings so encoded havea minimum hamming distance of k+1, and permit correction of (q−k−1)/2erroneous symbols. Block code may alternatively or additionally beimplemented using Golay coding, also known as binary Golay coding,Bose-Chaudhuri, Hocquenghuem (BCH) coding, multidimensional parity-checkcoding, and/or Hamming codes. An ECC may alternatively or additionallybe based on a convolutional code.

In an embodiment, and still referring to FIG. 5 , flight controller 112may include a reconfigurable hardware platform 512. A “reconfigurablehardware platform,” as used herein, is a component and/or unit ofhardware that may be reprogrammed, such that, for instance, a data pathbetween elements such as logic gates or other digital circuit elementsmay be modified to change an algorithm, state, logical sequence, or thelike of the component and/or unit. This may be accomplished with suchflexible high-speed computing fabrics as field-programmable gate arrays(FPGAs), which may include a grid of interconnected logic gates,connections between which may be severed and/or restored to program inmodified logic. Reconfigurable hardware platform 512 may be reconfiguredto enact any algorithm and/or algorithm selection process received fromanother computing device and/or created using machine-learningprocesses.

Still referring to FIG. 5 , reconfigurable hardware platform 512 mayinclude a logic component 516. As used in this disclosure a “logiccomponent” is a component that executes instructions on output language.For example, and without limitation, logic component may perform basicarithmetic, logic, controlling, input/output operations, and the likethereof. Logic component 516 may include any suitable processor, such aswithout limitation a component incorporating logical circuitry forperforming arithmetic and logical operations, such as an arithmetic andlogic unit (ALU), which may be regulated with a state machine anddirected by operational inputs from memory and/or sensors; logiccomponent 516 may be organized according to Von Neumann and/or Harvardarchitecture as a non-limiting example. Logic component 516 may include,incorporate, and/or be incorporated in, without limitation, amicrocontroller, microprocessor, digital signal processor (DSP), FieldProgrammable Gate Array (FPGA), Complex Programmable Logic Device(CPLD), Graphical Processing Unit (GPU), general purpose GPU, TensorProcessing Unit (TPU), analog or mixed signal processor, TrustedPlatform Module (TPM), a floating-point unit (FPU), and/or system on achip (SoC). In an embodiment, logic component 516 may include one ormore integrated circuit microprocessors, which may contain one or morecentral processing units, central processors, and/or main processors, ona single metal-oxide-semiconductor chip. Logic component 516 may beconfigured to execute a sequence of stored instructions to be performedon the output language and/or intermediate representation 508. Logiccomponent 516 may be configured to fetch and/or retrieve instructionfrom a memory cache, wherein a “memory cache,” as used in thisdisclosure, is a stored instruction set on flight controller 112. Logiccomponent 516 may be configured to decode instruction retrieved frommemory cache to opcodes and/or operands. Logic component 516 may beconfigured to execute instruction on intermediate representation 508and/or output language. For example, and without limitation, logiccomponent 516 may be configured to execute an addition operation onintermediate representation 508 and/or output language.

In an embodiment, and without limitation, logic component 516 may beconfigured to calculate a flight element 520. As used in this disclosurea “flight element” is an element of datum denoting a relative status ofaircraft. For example, and without limitation, flight element 520 maydenote one or more torques, thrusts, airspeed velocities, forces,altitudes, groundspeed velocities, directions during flight, directionsfacing, forces, orientations, and the like thereof. For example, andwithout limitation, flight element 520 may denote that aircraft iscruising at an altitude and/or with a sufficient magnitude of forwardthrust. As a further non-limiting example, flight status may denote thatis building thrust and/or groundspeed velocity in preparation for atakeoff. As a further non-limiting example, flight element 520 maydenote that aircraft is following a flight path accurately and/orsufficiently.

Still referring to FIG. 5 , flight controller 112 may include a chipsetcomponent 524. As used in this disclosure a “chipset component” is acomponent that manages data flow. In an embodiment, and withoutlimitation, chipset component 524 may include a northbridge data flowpath, wherein northbridge dataflow path may manage data flow from logiccomponent 516 to a high-speed device and/or component, such as a RAM,graphics controller, and the like thereof. In another embodiment, andwithout limitation, chipset component 524 may include a southbridge dataflow path, wherein southbridge dataflow path may manage data flow fromlogic component 516 to lower-speed peripheral buses, such as aperipheral component interconnect (PCI), industry standard architecture(ICA), and the like thereof. In an embodiment, and without limitation,southbridge data flow path may include managing data flow betweenperipheral connections such as ethernet, USB, audio devices, and thelike thereof. Additionally or alternatively, chipset component 524 maymanage data flow between logic component 516, memory cache, and a flightcomponent 108. As used in this disclosure a “flight component” is aportion of an aircraft that can be moved or adjusted to affect one ormore flight elements. For example, flight component 108 may include acomponent used to affect aircrafts' roll and pitch which may compriseone or more ailerons. As a further example, flight component 108 mayinclude a rudder to control yaw of an aircraft. In an embodiment,chipset component 524 may be configured to communicate with a pluralityof flight components as a function of flight element 520. For example,and without limitation, chipset component 524 may transmit to anaircraft rotor to reduce torque of a first lift propulsor and increasethe forward thrust produced by a pusher component to perform a flightmaneuver.

In an embodiment, and still referring to FIG. 5 , flight controller 112is configured generate an autonomous function. As used in thisdisclosure an “autonomous function” is a mode and/or function of flightcontroller 112 that controls aircraft automatically. For example, andwithout limitation, autonomous function may perform one or more aircraftmaneuvers, take offs, landings, altitude adjustments, flight levelingadjustments, turns, climbs, and/or descents. As a further non-limitingexample, autonomous function may adjust one or more airspeed velocities,thrusts, torques, and/or groundspeed velocities. As a furthernon-limiting example, autonomous function may perform one or more flightpath corrections and/or flight path modifications as a function offlight element 520. In an embodiment, autonomous function may includeone or more modes of autonomy such as, but not limited to, autonomousmode, semi-autonomous mode, and/or non-autonomous mode. As used in thisdisclosure “autonomous mode” is a mode that automatically adjusts and/orcontrols aircraft and/or the maneuvers of aircraft in its entirety. Forexample, autonomous mode may denote that flight controller 112 willadjust aircraft. As used in this disclosure a “semi-autonomous mode” isa mode that automatically adjusts and/or controls a portion and/orsection of aircraft.

In an embodiment, and still referring to FIG. 5 , flight controller 112generates autonomous function as a function of an autonomousmachine-learning model. As used in this disclosure an “autonomousmachine-learning model” is a machine-learning model to produce anautonomous function output given flight element 520 and pilot override528 as inputs; this is in contrast to a non-machine learning softwareprogram where the commands to be executed are determined in advance by auser and written in a programming language. As used in this disclosure a“pilot override switch” is an element of datum representing one or morefunctions a pilot does to claim flight control of aircraft 100. Forexample, pilot override 528 may denote that a pilot is gaining controland/or maneuvering ailerons, rudders and/or propulsors. In anembodiment, pilot override 528 must include an implicit signal and/or anexplicit signal. For example, and without limitation, pilot override 528may include an explicit signal, wherein pilot explicitly states desirefor control. As a further non-limiting example, pilot override 528 mayinclude an explicit signal directing flight controller 112 to controland/or maintain entire aircraft, and/or entire flight plan. As a furthernon-limiting example, pilot override 528 may include an implicit signal,wherein flight controller 112 detects a malfunction, torque alteration,flight path deviation, and the like thereof. In an embodiment, andwithout limitation, pilot override 528 may include one or more explicitsignals to reduce torque, and/or one or more implicit signals thattorque may be reduced due to reduction of airspeed velocity. In anembodiment, and without limitation, pilot override 528 may include oneor more local and/or global signals. For example, and withoutlimitation, pilot override 528 may include a local signal that istransmitted by a pilot and/or crew member. As a further non-limitingexample, pilot override 528 may include a global signal that istransmitted by air traffic control and/or one or more remote users thatare in communication with pilot of aircraft.

Still referring to FIG. 5 , autonomous machine-learning model mayinclude one or more autonomous machine-learning processes such assupervised, unsupervised, or reinforcement machine-learning processesthat flight controller 112 and/or a remote device may or may not use inthe generation of autonomous function. As used in this disclosure“remote device” is an external device to flight controller 112.Additionally or alternatively, autonomous machine-learning model mayinclude one or more autonomous machine-learning processes that afield-programmable gate array (FPGA) may or may not use in thegeneration of autonomous function. Autonomous machine-learning processmay include, without limitation machine learning processes such assimple linear regression, multiple linear regression, polynomialregression, support vector regression, ridge regression, lassoregression, elastic net regression, decision tree regression, randomforest regression, logistic regression, logistic classification,K-nearest neighbors, support vector machines, kernel support vectormachines, naïve bayes, decision tree classification, random forestclassification, K-means clustering, hierarchical clustering,dimensionality reduction, principal component analysis, lineardiscriminant analysis, kernel principal component analysis, Q-learning,State Action Reward State Action (SARSA), Deep-Q network, Markovdecision processes, Deep Deterministic Policy Gradient (DDPG), or thelike thereof.

In an embodiment, and still referring to FIG. 5 , autonomous machinelearning model may be trained as a function of autonomous training data,wherein autonomous training data may correlate a flight element, pilotsignal, and/or simulation data to an autonomous function. For example,and without limitation, a flight element of an airspeed velocity, apilot signal of limited and/or no control of propulsors, and asimulation data of required airspeed velocity to reach the destinationmay result in an autonomous function that may include a semi-autonomousmode to increase thrust of propulsors. Autonomous training data may bereceived as a function of user-entered valuations of flight elements,pilot signals, simulation data, and/or autonomous functions. Flightcontroller 112 may receive autonomous training data by receivingcorrelations of flight element, pilot signal, and/or simulation data toan autonomous function that were previously received and/or determinedduring a previous iteration of generation of autonomous function.Autonomous training data may be received by one or more remote devicesand/or FPGAs that at least correlate a flight element, pilot override,and/or simulation data to an autonomous function. Autonomous trainingdata may be received in the form of one or more user-enteredcorrelations of a flight element, pilot override, and/or simulation datato an autonomous function.

Still referring to FIG. 5 , flight controller 112 may receive autonomousmachine-learning model from a remote device and/or FPGA that utilizesone or more autonomous machine learning processes, wherein a remotedevice and an FPGA is described above in detail. For example, andwithout limitation, a remote device may include a computing device,external device, processor, FPGA, microprocessor, and the like thereof.Remote device and/or FPGA may perform autonomous machine-learningprocess using autonomous training data to generate autonomous functionand transmit output to flight controller 112. Remote device and/or FPGAmay transmit a signal, bit, datum, or parameter to flight controller 112that at least relates to autonomous function. Additionally oralternatively, remote device and/or FPGA may provide an updatedmachine-learning model. For example, and without limitation, an updatedmachine-learning model may be comprised of a firmware update, a softwareupdate, an autonomous machine-learning process correction, and the likethereof. As a non-limiting example, a software update may incorporate anew simulation data that relates to a modified flight element.Additionally or alternatively, the updated machine learning model may betransmitted to remote device and/or FPGA, wherein remote device and/orFPGA may replace autonomous machine-learning model with updatedmachine-learning model and generate the autonomous function as afunction of flight element, pilot override, and/or simulation data usingthe updated machine-learning model. Updated machine-learning model maybe transmitted by remote device and/or FPGA and received by flightcontroller 112 as a software update, firmware update, or correctedautonomous machine-learning model. For example, and without limitationautonomous machine learning model may utilize a neural netmachine-learning process, wherein updated machine-learning model mayincorporate a gradient boosting machine-learning process.

Still referring to FIG. 5 , flight controller 112 may include, beincluded in, and/or communicate with a mobile device such as a mobiletelephone or smartphone. Further, flight controller may communicate withone or more additional devices as described below in further detail viaa network interface device. Network interface device may be utilized forcommutatively connecting a flight controller to one or more of a varietyof networks, and one or more devices. Examples of a network interfacedevice may include, but are not limited to, a network interface card(e.g., a mobile network interface card, a LAN card), a modem, and anycombination thereof. Examples of a network may include, but are notlimited to, a wide area network (e.g., the Internet, an enterprisenetwork), a local area network (e.g., a network associated with anoffice, a building, a campus or other relatively small geographicspace), a telephone network, a data network associated with atelephone/voice provider (e.g., a mobile communications provider dataand/or voice network), a direct connection between two computingdevices, and any combinations thereof. Network may include any networktopology and can may employ a wired and/or a wireless mode ofcommunication.

In an embodiment, and still referring to FIG. 5 , flight controller 112may include, but is not limited to, for example, a cluster of flightcontrollers in a first location and a second flight controller orcluster of flight controllers in a second location. Flight controller112 may include one or more flight controllers dedicated to datastorage, security, distribution of traffic for load balancing, and thelike. Flight controller 112 may be configured to distribute one or morecomputing tasks as described below across a plurality of flightcontrollers, which may operate in parallel, in series, redundantly, orin any other manner used for distribution of tasks or memory betweencomputing devices. For example, and without limitation, flightcontroller 112 may implement a control algorithm to distribute and/orcommand plurality of flight controllers. As used in this disclosure a“control algorithm” is a finite sequence of well-defined computerimplementable instructions that may determine flight component ofplurality of flight components to be adjusted. For example, and withoutlimitation, control algorithm may include one or more algorithms thatreduce and/or prevent aviation asymmetry. As a further non-limitingexample, control algorithms may include one or more models generated asa function of a software including, but not limited to Simulink byMathWorks, Natick, Mass., USA. In an embodiment, and without limitation,control algorithm may be configured to generate an auto-code, wherein an“auto-code,” is used herein, is a code and/or algorithm that isgenerated as a function of one or more models and/or software's. Inanother embodiment, control algorithm may be configured to produce asegmented control algorithm. As used in this disclosure a “segmentedcontrol algorithm” is control algorithm that has been separated and/orparsed into discrete sections. For example, and without limitation,segmented control algorithm may parse control algorithm into two or moresegments, wherein each segment of control algorithm may be performed byone or more flight controllers operating on distinct flight components.

In an embodiment, and still referring to FIG. 5 , control algorithm maybe configured to determine a segmentation boundary as a function ofsegmented control algorithm. As used in this disclosure a “segmentationboundary” is a limit and/or delineation associated with segments of thesegmented control algorithm. For example, and without limitation,segmentation boundary may denote that a segment in the control algorithmhas a first starting section and/or a first ending section. As a furthernon-limiting example, segmentation boundary may include one or moreboundaries associated with an ability of flight component 108. In anembodiment, control algorithm may be configured to create an optimizedsignal communication as a function of segmentation boundary. Forexample, and without limitation, optimized signal communication mayinclude identifying the discrete timing required to transmit and/orreceive one or more segmentation boundaries. In an embodiment, andwithout limitation, creating optimized signal communication furthercomprises separating a plurality of signal codes across plurality offlight controllers. For example, and without limitation, plurality offlight controllers may include one or more formal networks, whereinformal networks transmit data along an authority chain and/or arelimited to task-related communications. As a further non-limitingexample, communication network may include informal networks, whereininformal networks transmit data in any direction. In an embodiment, andwithout limitation, plurality of flight controllers may include a chainpath, wherein a “chain path,” as used herein, is a linear communicationpath comprising a hierarchy that data may flow through. In anembodiment, and without limitation, plurality of flight controllers mayinclude an all-channel path, wherein an “all-channel path,” as usedherein, is a communication path that is not restricted to a particulardirection. For example, and without limitation, data may be transmittedupward, downward, laterally, and the like thereof. In an embodiment, andwithout limitation, plurality of flight controllers may include one ormore neural networks that assign a weighted value to a transmitteddatum. For example, and without limitation, a weighted value may beassigned as a function of one or more signals denoting that a flightcomponent is malfunctioning and/or in a failure state.

Still referring to FIG. 5 , plurality of flight controllers may includea master bus controller. As used in this disclosure a “master buscontroller” is one or more devices and/or components that are connectedto a bus to initiate a direct memory access transaction, wherein a busis one or more terminals in a bus architecture. Master bus controllermay communicate using synchronous and/or asynchronous bus controlprotocols. In an embodiment, master bus controller may include flightcontroller 112. In another embodiment, master bus controller may includeone or more universal asynchronous receiver-transmitters (UART). Forexample, and without limitation, master bus controller may include oneor more bus architectures that allow a bus to initiate a direct memoryaccess transaction from one or more buses in the bus architectures. As afurther non-limiting example, master bus controller may include one ormore peripheral devices and/or components to communicate with anotherperipheral device and/or component and/or master bus controller. In anembodiment, master bus controller may be configured to perform busarbitration. As used in this disclosure “bus arbitration” is methodand/or scheme to prevent multiple buses from attempting to communicatewith and/or connect to master bus controller. For example, and withoutlimitation, bus arbitration may include one or more schemes such as asmall computer interface system, wherein a small computer interfacesystem is a set of standards for physical connecting and transferringdata between peripheral devices and master bus controller by definingcommands, protocols, electrical, optical, and/or logical interfaces. Inan embodiment, master bus controller may receive intermediaterepresentation 508 and/or output language from logic component 516,wherein output language may include one or more analog-to-digitalconversions, low bit rate transmissions, message encryptions, digitalsignals, binary signals, logic signals, analog signals, and the likethereof described above in detail.

Still referring to FIG. 5 , master bus controller may communicate with aslave bus. As used in this disclosure a “slave bus” is one or moreperipheral devices and/or components that initiate a bus transfer. Forexample, and without limitation, slave bus may receive one or morecontrols and/or asymmetric communications from master bus controller,wherein slave bus transfers data stored to master bus controller. In anembodiment, and without limitation, slave bus may include one or moreinternal buses, such as but not limited to a/an internal data bus,memory bus, system bus, front-side bus, and the like thereof. In anotherembodiment, and without limitation, slave bus may include one or moreexternal buses such as external flight controllers, external computers,remote devices, printers, aircraft computer systems, flight controlsystems, and the like thereof.

In an embodiment, and still referring to FIG. 5 , control algorithm mayoptimize signal communication as a function of determining one or morediscrete timings. For example, and without limitation master buscontroller may synchronize timing of the segmented control algorithm byinjecting high priority timing signals on a bus of master bus control.As used in this disclosure a “high priority timing signal” isinformation denoting that the information is important. For example, andwithout limitation, high priority timing signal may denote that asection of control algorithm is of high priority and should be analyzedand/or transmitted prior to any other sections being analyzed and/ortransmitted. In an embodiment, high priority timing signal may includeone or more priority packets. As used in this disclosure a “prioritypacket” is a formatted unit of data that is communicated betweenplurality of flight controllers. For example, and without limitation,priority packet may denote that a section of control algorithm should beused and/or is of greater priority than other sections.

Still referring to FIG. 5 , flight controller 112 may also beimplemented using a “shared nothing” architecture in which data iscached at the worker, in an embodiment, this may enable scalability ofaircraft and/or computing device. Flight controller 112 may include adistributer flight controller. As used in this disclosure a “distributerflight controller” is a component that adjusts and/or controls aplurality of flight components as a function of a plurality of flightcontrollers. For example, distributer flight controller may include aflight controller that communicates with a plurality of additionalflight controllers and/or clusters of flight controllers. In anembodiment, distributed flight control may include one or more neuralnetworks. For example, neural network also known as an artificial neuralnetwork, is a network of “nodes,” or data structures having one or moreinputs, one or more outputs, and a function determining outputs based oninputs. Such nodes may be organized in a network, such as withoutlimitation a convolutional neural network, including an input layer ofnodes, one or more intermediate layers, and an output layer of nodes.Connections between nodes may be created via the process of “training”the network, in which elements from a training dataset are applied toinput nodes, a suitable training algorithm (such as Levenberg-Marquardt,conjugate gradient, simulated annealing, or other algorithms) is thenused to adjust connections and weights between nodes in adjacent layersof neural network to produce the desired values at output nodes. Thisprocess is sometimes referred to as deep learning.

Still referring to FIG. 5 , a node may include, without limitation aplurality of inputs x_(i) that may receive numerical values from inputsto a neural network containing node and/or from other nodes. Node mayperform a weighted sum of inputs using weights w_(i) that are multipliedby respective inputs x_(i). Additionally or alternatively, a bias b maybe added to the weighted sum of inputs such that an offset is added toeach unit in neural network layer that is independent of input to thelayer. Weighted sum may then be input into a function ω, which maygenerate one or more outputs y. Weight w_(i) applied to an input x_(i)may indicate whether input is “excitatory,” indicating that it hasstrong influence on one or more outputs y, for instance by thecorresponding weight having a large numerical value, and/or a“inhibitory,” indicating it has a weak effect influence on one moreinputs y, for instance by the corresponding weight having a smallnumerical value. Values of weights w_(i) may be determined by training aneural network using training data, which may be performed using anysuitable process as described above. In an embodiment, and withoutlimitation, a neural network may receive semantic units as inputs andoutput vectors representing such semantic units according to weightsw_(i) that are derived using machine-learning processes as described inthis disclosure.

Still referring to FIG. 5 , flight controller 112 may include asub-controller 532. As used in this disclosure a “sub-controller” is acontroller and/or component that is part of a distributed controller asdescribed above; for instance, flight controller 112 may be and/orinclude a distributed flight controller made up of one or moresub-controllers. For example, and without limitation, sub-controller 532may include any controllers and/or components thereof that are similarto distributed flight controller and/or flight controller as describedabove. Sub-controller 532 may include any component of any flightcontroller as described above. Sub-controller 532 may be implemented inany manner suitable for implementation of a flight controller asdescribed above. As a further non-limiting example, sub-controller 532may include one or more processors, logic components and/or computingdevices capable of receiving, processing, and/or transmitting dataacross distributed flight controller as described above. As a furthernon-limiting example, sub-controller 532 may include a controller thatreceives a signal from a first flight controller and/or firstdistributed flight controller component and transmits signal to aplurality of additional sub-controllers and/or flight components.

Still referring to FIG. 5 , flight controller may include aco-controller 536. As used in this disclosure a “co-controller” is acontroller and/or component that joins flight controller 112 ascomponents and/or nodes of a distributer flight controller as describedabove. For example, and without limitation, co-controller 536 mayinclude one or more controllers and/or components that are similar toflight controller 112. As a further non-limiting example, co-controller536 may include any controller and/or component that joins flightcontroller 112 to distributer flight controller. As a furthernon-limiting example, co-controller 536 may include one or moreprocessors, logic components and/or computing devices capable ofreceiving, processing, and/or transmitting data to and/or from flightcontroller 112 to distributed flight control system. Co-controller 536may include any component of any flight controller as described above.Co-controller 536 may be implemented in any manner suitable forimplementation of a flight controller as described above.

In an embodiment, and with continued reference to FIG. 5 , flightcontroller 112 may be designed and/or configured to perform any method,method step, or sequence of method steps in any embodiment described inthis disclosure, in any order and with any degree of repetition. Forinstance, flight controller 112 may be configured to perform a singlestep or sequence repeatedly until a desired or commanded outcome isachieved; repetition of a step or a sequence of steps may be performediteratively and/or recursively using outputs of previous repetitions asinputs to subsequent repetitions, aggregating inputs and/or outputs ofrepetitions to produce an aggregate result, reduction or decrement ofone or more variables such as global variables, and/or division of alarger processing task into a set of iteratively addressed smallerprocessing tasks. Flight controller may perform any step or sequence ofsteps as described in this disclosure in parallel, such assimultaneously and/or substantially simultaneously performing a step twoor more times using two or more parallel threads, processor cores, orthe like; division of tasks between parallel threads and/or processesmay be performed according to any protocol suitable for division oftasks between iterations. Persons skilled in the art, upon reviewingentirety of this disclosure, will be aware of various ways in whichsteps, sequences of steps, processing tasks, and/or data may besubdivided, shared, or otherwise dealt with using iteration, recursion,and/or parallel processing.

Referring now to FIG. 6 , an exemplary embodiment of a machine-learningmodule 600 that may perform one or more machine-learning processes asdescribed in this disclosure is illustrated. Machine-learning module mayperform determinations, classification, and/or analysis steps, methods,processes, or the like as described in this disclosure using machinelearning processes. A “machine learning process,” as used in thisdisclosure, is a process that automatedly uses training data 604 togenerate an algorithm that will be performed by a computingdevice/module to produce outputs 608 given data provided as inputs 612;this is in contrast to a non-machine learning software program wherecommands to be executed are determined in advance by a user and writtenin a programming language.

Still referring to FIG. 6 , “training data,” as used herein, is datacontaining correlations that a machine-learning process may use to modelrelationships between two or more categories of data elements. Forinstance, and without limitation, training data 604 may include aplurality of data entries, each entry representing a set of dataelements that were recorded, received, and/or generated together; dataelements may be correlated by shared existence in a given data entry, byproximity in a given data entry, or the like. Multiple data entries intraining data 604 may evince one or more trends in correlations betweencategories of data elements; for instance, and without limitation, ahigher value of a first data element belonging to a first category ofdata element may tend to correlate to a higher value of a second dataelement belonging to a second category of data element, indicating apossible proportional or other mathematical relationship linking valuesbelonging to the two categories. Multiple categories of data elementsmay be related in training data 604 according to various correlations;correlations may indicate causative and/or predictive links betweencategories of data elements, which may be modeled as relationships suchas mathematical relationships by machine-learning processes as describedin further detail below. Training data 604 may be formatted and/ororganized by categories of data elements, for instance by associatingdata elements with one or more descriptors corresponding to categoriesof data elements. As a non-limiting example, training data 604 mayinclude data entered in standardized forms by persons or processes, suchthat entry of a given data element in a given field in a form may bemapped to one or more descriptors of categories. Elements in trainingdata 604 may be linked to descriptors of categories by tags, tokens, orother data elements; for instance, and without limitation, training data604 may be provided in fixed-length formats, formats linking positionsof data to categories such as comma-separated value (CSV) formats and/orself-describing formats such as extensible markup language (XML),JavaScript Object Notation (JSON), or the like, enabling processes ordevices to detect categories of data.

Alternatively or additionally, and continuing to refer to FIG. 6 ,training data 604 may include one or more elements that are notcategorized; that is, training data 604 may not be formatted or containdescriptors for some elements of data. Machine-learning algorithmsand/or other processes may sort training data 604 according to one ormore categorizations using, for instance, natural language processingalgorithms, tokenization, detection of correlated values in raw data andthe like; categories may be generated using correlation and/or otherprocessing algorithms. As a non-limiting example, in a corpus of text,phrases making up a number “n” of compound words, such as nouns modifiedby other nouns, may be identified according to a statisticallysignificant prevalence of n-grams containing such words in a particularorder; such an n-gram may be categorized as an element of language suchas a “word” to be tracked similarly to single words, generating a newcategory as a result of statistical analysis. Similarly, in a data entryincluding some textual data, a person's name may be identified byreference to a list, dictionary, or other compendium of terms,permitting ad-hoc categorization by machine-learning algorithms, and/orautomated association of data in the data entry with descriptors or intoa given format. The ability to categorize data entries automatedly mayenable the same training data 604 to be made applicable for two or moredistinct machine-learning algorithms as described in further detailbelow. Training data 604 used by machine-learning module 600 maycorrelate any input data as described in this disclosure to any outputdata as described in this disclosure. As a non-limiting illustrativeexample flight elements and/or pilot signals may be inputs, wherein anoutput is an autonomous function.

Further referring to FIG. 6 , training data may be filtered, sorted,and/or selected using one or more supervised and/or unsupervisedmachine-learning processes and/or models as described in further detailbelow; such models may include without limitation a training dataclassifier %112. Training data classifier %112 may include a“classifier,” which as used in this disclosure is a machine-learningmodel as defined below, such as a mathematical model, neural net, orprogram generated by a machine learning algorithm known as a“classification algorithm,” as described in further detail below, thatsorts inputs into categories or bins of data, outputting categories orbins of data and/or labels associated therewith. A classifier may beconfigured to output at least a datum that labels or otherwiseidentifies a set of data that are clustered together, found to be closeunder a distance metric as described below, or the like.Machine-learning module 600 may generate a classifier using aclassification algorithm, defined as a process whereby a computingdevice and/or any module and/or component operating thereon derives aclassifier from training data 604. Classification may be performedusing, without limitation, linear classifiers such as without limitationlogistic regression and/or naive Bayes classifiers, nearest neighborclassifiers such as k-nearest neighbors classifiers, support vectormachines, least squares support vector machines, fisher's lineardiscriminant, quadratic classifiers, decision trees, boosted trees,random forest classifiers, learning vector quantization, and/or neuralnetwork-based classifiers. As a non-limiting example, training dataclassifier %112 may classify elements of training data to sub-categoriesof flight elements such as torques, forces, thrusts, directions, and thelike thereof.

Still referring to FIG. 6 , machine-learning module 600 may beconfigured to perform a lazy-learning process 620 and/or protocol, whichmay alternatively be referred to as a “lazy loading” or“call-when-needed” process and/or protocol, may be a process wherebymachine learning is conducted upon receipt of an input to be convertedto an output, by combining input and training set to derive thealgorithm to be used to produce output on demand. For instance, aninitial set of simulations may be performed to cover an initialheuristic and/or “first guess” at an output and/or relationship. As anon-limiting example, an initial heuristic may include a ranking ofassociations between inputs and elements of training data 604. Heuristicmay include selecting some number of highest-ranking associations and/ortraining data 604 elements. Lazy learning may implement any suitablelazy learning algorithm, including without limitation a K-nearestneighbors algorithm, a lazy naïve Bayes algorithm, or the like; personsskilled in the art, upon reviewing entirety of this disclosure, will beaware of various lazy-learning algorithms that may be applied togenerate outputs as described in this disclosure, including withoutlimitation lazy learning applications of machine-learning algorithms asdescribed in further detail below.

Alternatively or additionally, and with continued reference to FIG. 6 ,machine-learning processes as described in this disclosure may be usedto generate machine-learning models 624. A “machine-learning model,” asused in this disclosure, is a mathematical and/or algorithmicrepresentation of a relationship between inputs and outputs, asgenerated using any machine-learning process including withoutlimitation any process as described above and stored in memory; an inputis submitted to a machine-learning model 624 once created, whichgenerates an output based on the relationship that was derived. Forinstance, and without limitation, a linear regression model, generatedusing a linear regression algorithm, may compute a linear combination ofinput data using coefficients derived during machine-learning processesto calculate an output datum. As a further non-limiting example, amachine-learning model 624 may be generated by creating an artificialneural network, such as a convolutional neural network comprising aninput layer of nodes, one or more intermediate layers, and an outputlayer of nodes. Connections between nodes may be created via process of“training” the network, in which elements from a training data 604 setare applied to input nodes, a suitable training algorithm (such asLevenberg-Marquardt, conjugate gradient, simulated annealing, or otheralgorithms) is then used to adjust connections and weights between nodesin adjacent layers of neural network to produce desired values at outputnodes. This process is sometimes referred to as deep learning.

Still referring to FIG. 6 , machine-learning algorithms may include atleast a supervised machine-learning process 628. At least a supervisedmachine-learning process 628, as defined herein, may include algorithmsthat receive a training set relating a number of inputs to a number ofoutputs, and seek to find one or more mathematical relations relatinginputs to outputs, where each of the one or more mathematical relationsis optimal according to some criterion specified to the algorithm usingsome scoring function. For instance, a supervised learning algorithm mayinclude flight elements and/or pilot signals as described above asinputs, autonomous functions as outputs, and a scoring functionrepresenting a desired form of relationship to be detected betweeninputs and outputs; scoring function may, for instance, seek to maximizethe probability that a given input and/or combination of elements inputsis associated with a given output to minimize the probability that agiven input is not associated with a given output. Scoring function maybe expressed as a risk function representing an “expected loss” of analgorithm relating inputs to outputs, where loss is computed as an errorfunction representing a degree to which a prediction generated by therelation is incorrect when compared to a given input-output pairprovided in training data 604. Persons skilled in the art, uponreviewing entirety of this disclosure, will be aware of various possiblevariations of at least a supervised machine-learning process 628 thatmay be used to determine relation between inputs and outputs. Supervisedmachine-learning processes may include classification algorithms asdefined above.

Further referring to FIG. 6 , machine learning processes may include atleast an unsupervised machine-learning processes 632. An unsupervisedmachine-learning process, as used herein, is a process that derivesinferences in datasets without regard to labels; as a result, anunsupervised machine-learning process may be free to discover anystructure, relationship, and/or correlation provided in the data.Unsupervised processes may not require a response variable; unsupervisedprocesses may be used to find interesting patterns and/or inferencesbetween variables, to determine a degree of correlation between two ormore variables, or the like.

Still referring to FIG. 6 , machine-learning module 600 may be designedand configured to create a machine-learning model 624 using techniquesfor development of linear regression models. Linear regression modelsmay include ordinary least squares regression, which aims to minimizethe square of the difference between predicted outcomes and actualoutcomes according to an appropriate norm for measuring such adifference (e.g. a vector-space distance norm); coefficients ofresulting linear equation may be modified to improve minimization.Linear regression models may include ridge regression methods, where thefunction to be minimized may include the least-squares function plusterm multiplying the square of each coefficient by a scalar amount topenalize large coefficients. Linear regression models may include leastabsolute shrinkage and selection operator (LASSO) models, in which ridgeregression is combined with multiplying the least-squares term by afactor of 1 divided by double the number of samples. Linear regressionmodels may include a multi-task lasso model wherein the norm applied inthe least-squares term of the lasso model is the Frobenius normamounting to the square root of the sum of squares of all terms. Linearregression models may include the elastic net model, a multi-taskelastic net model, a least angle regression model, a LARS lasso model,an orthogonal matching pursuit model, a Bayesian regression model, alogistic regression model, a stochastic gradient descent model, aperceptron model, a passive aggressive algorithm, a robustnessregression model, a Huber regression model, or any other suitable modelthat may occur to persons skilled in the art upon reviewing the entiretyof this disclosure. Linear regression models may be generalized in anembodiment to polynomial regression models, whereby a polynomialequation (e.g. a quadratic, cubic or higher-order equation) providing abest predicted output/actual output fit is sought; similar methods tothose described above may be applied to minimize error functions, aswill be apparent to persons skilled in the art upon reviewing theentirety of this disclosure.

Continuing to refer to FIG. 6 , machine-learning algorithms may include,without limitation, linear discriminant analysis. Machine-learningalgorithm may include quadratic discriminate analysis. Machine-learningalgorithms may include kernel ridge regression. Machine-learningalgorithms may include support vector machines, including withoutlimitation support vector classification-based regression processes.Machine-learning algorithms may include stochastic gradient descentalgorithms, including classification and regression algorithms based onstochastic gradient descent. Machine-learning algorithms may includenearest neighbors algorithms. Machine-learning algorithms may includeGaussian processes such as Gaussian Process Regression. Machine-learningalgorithms may include cross-decomposition algorithms, including partialleast squares and/or canonical correlation analysis. Machine-learningalgorithms may include naïve Bayes methods. Machine-learning algorithmsmay include algorithms based on decision trees, such as decision treeclassification or regression algorithms. Machine-learning algorithms mayinclude ensemble methods such as bagging meta-estimator, forest ofrandomized tress, AdaBoost, gradient tree boosting, and/or votingclassifier methods. Machine-learning algorithms may include neural netalgorithms, including convolutional neural net processes.

Now referring to FIG. 7 , an exemplary embodiment of a method 700 forflight transition of an eVTOL aircraft. eVTOL aircraft may include,without limitation, any of the aircraft as disclosed herein anddescribed above with reference to at least FIG. 1 .

Still referring to FIG. 7 , at step 705, method 700 includes a flightcontroller, incorporated in an electric vertical takeoff and landing(eVTOL) aircraft having a plurality of propulsors configured to rotatebetween a lift position to a forward thrust position, is provided.Flight controller is communicatively connected to pilot override switch.Pilot override switch as disclosed herein and described above withreference to at least FIG. 1 and FIG. 2 . Flight controller may be anyone of flight controllers as disclosed herein and described above withreference to at least FIG. 1 , FIG. 4 and FIG. 5 .

Still referring to FIG. 7 , at step 710, method 700 includes the flightcontroller identifies a flight transition point for aircraft totransition from vertical to horizontal flight. Plurality of propulsorsmay be any one of flight controllers as disclosed herein and describedabove with reference to at least FIG. 1 , FIG. 4 and FIG. 5 . Flightcontroller may be any one of flight controllers as disclosed herein anddescribed above with reference to at least FIG. 1 , FIG. 4 and FIG. 5 .

Still referring to FIG. 7 , at step 715, method 700 includes flightcontroller initiates rotation of plurality of propulsors about an axisof the fuselage as a function of the flight transition point. Pluralityof propulsors may be any one of propulsors as disclosed herein anddescribed above with reference to at least FIG. 1 , FIG. 4 and FIG. 5 .Flight controller may be any one of flight controllers as disclosedherein and described above with reference to at least FIG. 1 , FIG. 4and FIG. 5 .

Still referring to FIG. 7 , at step 720, method 700 includes flightcontroller terminates rotation of plurality of propulsors about an axisof the fuselage once the desired flight angle is reached, as a functionof the flight transition point. Plurality of propulsors may be any oneof propulsors as disclosed herein and described above with reference toat least FIG. 1 , FIG. 4 and FIG. 5 . Flight controller may be any oneof flight controllers as disclosed herein and described above withreference to at least FIG. 1 , FIG. 4 and FIG. 5 .

It is to be noted that any one or more of the aspects and embodimentsdescribed herein may be conveniently implemented using one or moremachines (e.g., one or more computing devices that are utilized as auser computing device for an electronic document, one or more serverdevices, such as a document server, etc.) programmed according to theteachings of the present specification, as will be apparent to those ofordinary skill in computer art. Appropriate software coding can readilybe prepared by skilled programmers based on the teachings of the presentdisclosure, as will be apparent to those of ordinary skill in thesoftware art. Aspects and implementations discussed above employingsoftware and/or software modules may also include appropriate hardwarefor assisting in the implementation of the machine executableinstructions of software and/or software module.

Such software may be a computer program product that employs amachine-readable storage medium. A machine-readable storage medium maybe any medium that is capable of storing and/or encoding a sequence ofinstructions for execution by a machine (e.g., a computing device) andthat causes the machine to perform any one of the methodologies and/orembodiments described herein. Examples of a machine-readable storagemedium may include, but are not limited to, a magnetic disk, an opticaldisc (e.g., CD, CD-R, DVD, DVD-R, etc.), a magneto-optical disk, aread-only memory “ROM” device, a random-access memory “RAM” device, amagnetic card, an optical card, a solid-state memory device, an EPROM,an EEPROM, and any combinations thereof. A machine-readable medium, asused herein, may include a single medium as well as a collection ofphysically separate media, such as, for example, a collection of compactdiscs or one or more hard disk drives in combination with a computermemory. As used herein, a machine-readable storage medium does notinclude transitory forms of signal transmission.

Such software may also include information (e.g., data) carried as adata signal on a data carrier, such as a carrier wave. For example,machine-executable information may be included as a data-carrying signalembodied in a data carrier in which signal encodes a sequence ofinstruction, or portion thereof, for execution by a machine (e.g., acomputing device) and any related information (e.g., data structures anddata) that causes the machine to perform any one of the methodologiesand/or embodiments described herein.

Examples of a computing device may include, but are not limited to, anelectronic book reading device, a computer workstation, a terminalcomputer, a server computer, a handheld device (e.g., a tablet computer,a smartphone, etc.), a web appliance, a network router, a networkswitch, a network bridge, any machine capable of executing a sequence ofinstructions that specify an action to be taken by that machine, and anycombinations thereof. In one example, a computing device may includeand/or be included in a kiosk.

FIG. 8 shows a diagrammatic representation of one embodiment of acomputing device in exemplary form of a computer system 800 within whicha set of instructions for causing a control system to perform any one ormore of the aspects and/or methodologies of the present disclosure maybe executed. It is also contemplated that multiple computing devices maybe utilized to implement a specially configured set of instructions forcausing one or more of the devices to perform any one or more of theaspects and/or methodologies of the present disclosure. Computer system800 may include a processor 804 and a memory 808 that communicate witheach other, and with other components, via a bus 812. Bus 812 mayinclude any of several types of bus structures including, but notlimited to, a memory bus, a memory controller, a peripheral bus, a localbus, and any combinations thereof, using any of a variety of busarchitectures.

Processor 804 may include any suitable processor, such as withoutlimitation a processor incorporating logical circuitry for performingarithmetic and logical operations, such as an arithmetic and logic unit(ALU), which may be regulated with a state machine and directed byoperational inputs from memory and/or sensors; processor 804 may beorganized according to Von Neumann and/or Harvard architecture as anon-limiting example. Processor 804 may include, incorporate, and/or beincorporated in, without limitation, a microcontroller, microprocessor,digital signal processor (DSP), Field Programmable Gate Array (FPGA),Complex Programmable Logic Device (CPLD), Graphical Processing Unit(GPU), general purpose GPU, Tensor Processing Unit (TPU), analog ormixed signal processor, Trusted Platform Module (TPM), a floating-pointunit (FPU), and/or system on a chip (SoC).

Memory 808 may include various components (e.g., machine-readable media)including, but not limited to, a random-access memory component, a readonly component, and any combinations thereof. In one example, a basicinput/output system 816 (BIOS), including basic routines that help totransfer information between elements within computer system 800, suchas during start-up, may be stored in memory 808. Memory 808 may alsoinclude (e.g., stored on one or more machine-readable media)instructions (e.g., software) 820 embodying any one or more of theaspects and/or methodologies of the present disclosure. In anotherexample, memory 808 may further include any number of program modulesincluding, but not limited to, an operating system, one or moreapplication programs, other program modules, program data, and anycombinations thereof.

Computer system 800 may also include a storage device 824. Examples of astorage device (e.g., storage device 824) include, but are not limitedto, a hard disk drive, a magnetic disk drive, an optical disc drive incombination with an optical medium, a solid-state memory device, and anycombinations thereof. Storage device 824 may be connected to bus 812 byan appropriate interface (not shown). Example interfaces include, butare not limited to, SCSI, advanced technology attachment (ATA), serialATA, universal serial bus (USB), IEEE 1394 (FIREWIRE), and anycombinations thereof. In one example, storage device 824 (or one or morecomponents thereof) may be removably interfaced with computer system 800(e.g., via an external port connector (not shown)). Particularly,storage device 824 and an associated machine-readable medium 828 mayprovide nonvolatile and/or volatile storage of machine-readableinstructions, data structures, program modules, and/or other data forcomputer system 800. In one example, software 820 may reside, completelyor partially, within machine-readable medium 828. In another example,software 820 may reside, completely or partially, within processor 804.

Computer system 800 may also include an input device 832. In oneexample, a user of computer system 800 may enter commands and/or otherinformation into computer system 800 via input device 832. Examples ofan input device 832 include, but are not limited to, an alpha-numericinput device (e.g., a keyboard), a pointing device, a joystick, agamepad, an audio input device (e.g., a microphone, a voice responsesystem, etc.), a cursor control device (e.g., a mouse), a touchpad, anoptical scanner, a video capture device (e.g., a still camera, a videocamera), a touchscreen, and any combinations thereof. Input device 832may be interfaced to bus 812 via any of a variety of interfaces (notshown) including, but not limited to, a serial interface, a parallelinterface, a game port, a USB interface, a FIREWIRE interface, a directinterface to bus 812, and any combinations thereof. Input device 832 mayinclude a touch screen interface that may be a part of or separate fromdisplay 836, discussed further below. Input device 832 may be utilizedas a user selection device for selecting one or more graphicalrepresentations in a graphical interface as described above.

A user may also input commands and/or other information to computersystem 800 via storage device 824 (e.g., a removable disk drive, a flashdrive, etc.) and/or network interface device 840. A network interfacedevice, such as network interface device 840, may be utilized forconnecting computer system 800 to one or more of a variety of networks,such as network 844, and one or more remote devices 848 connectedthereto. Examples of a network interface device include, but are notlimited to, a network interface card (e.g., a mobile network interfacecard, a LAN card), a modem, and any combination thereof. Examples of anetwork include, but are not limited to, a wide area network (e.g., theInternet, an enterprise network), a local area network (e.g., a networkassociated with an office, a building, a campus or other relativelysmall geographic space), a telephone network, a data network associatedwith a telephone/voice provider (e.g., a mobile communications providerdata and/or voice network), a direct connection between two computingdevices, and any combinations thereof. A network, such as network 844,may employ a wired and/or a wireless mode of communication. In general,any network topology may be used. Information (e.g., data, software 820,etc.) may be communicated to and/or from computer system 800 via networkinterface device 840.

Computer system 800 may further include a video display adapter 852 forcommunicating a displayable image to a display device, such as displaydevice 836. Examples of a display device include, but are not limitedto, a liquid crystal display (LCD), a cathode ray tube (CRT), a plasmadisplay, a light emitting diode (LED) display, and any combinationsthereof. Display adapter 852 and display device 836 may be utilized incombination with processor 808 to provide graphical representations ofaspects of the present disclosure. In addition to a display device,computer system 800 may include one or more other peripheral outputdevices including, but not limited to, an audio speaker, a printer, andany combinations thereof. Such peripheral output devices may beconnected to bus 812 via a peripheral interface 856. Examples of aperipheral interface include, but are not limited to, a serial port, aUSB connection, a FIREWIRE connection, a parallel connection, and anycombinations thereof.

The foregoing has been a detailed description of illustrativeembodiments of the invention. Various modifications and additions can bemade without departing from the spirit and scope of this invention.Features of each of the various embodiments described above may becombined with features of other described embodiments as appropriate toprovide a multiplicity of feature combinations in associated newembodiments. Furthermore, while the foregoing describes a number ofseparate embodiments, what has been described herein is merelyillustrative of the application of the principles of the presentinvention. Additionally, although particular methods herein may beillustrated and/or described as being performed in a specific order, theordering is highly variable within ordinary skill to achieve systems andmethods according to the present disclosure. Accordingly, thisdescription is meant to be taken only by way of example, and not tootherwise limit the scope of this invention.

Exemplary embodiments have been disclosed above and illustrated in theaccompanying drawings. It will be understood by those skilled in the artthat various changes, omissions and additions may be made to that whichis specifically disclosed herein without departing from the spirit andscope of the present invention.

What is claimed is:
 1. A system for flight control of an electricvertical takeoff and landing (eVTOL) aircraft, the system comprising: afuselage; a plurality of laterally extending elements secured to thefuselage; a plurality of propulsors attached to the plurality oflaterally extending elements, wherein the plurality of propulsors areconfigured to rotate between a lift position to a forward thrustposition; a flight controller including a reconfigurable hardwareplatform, the reconfigurable hardware platform containing hardwarecircuitry configured to: identify a flight transition point; determine asegmentation boundary of a segmented control algorithm, wherein thesegmentation boundary includes a boundary associated with an ability ofa propulsor of the plurality of propulsors; distribute a plurality ofcommands based on the flight transition point and the segmentationboundary to a cluster of flight controllers, wherein each flightcontroller of the cluster of flight controllers operates a propulsor ofthe plurality of propulsors; perform a flight maneuver based on theplurality of commands, wherein performing a flight maneuver includesperforming a flight transition, wherein the flight transition includes:initiating rotation about an axis of the fuselage as a function of theflight transition point; and terminating rotation about the axis of thefuselage once a desired flight angle is reached.
 2. The system of claim1, further comprising a pilot override switch.
 3. The system of claim 1,wherein each propulsor of the plurality of propulsors is attached to theaircraft by a rotating actuator.
 4. The system of claim 1, wherein theplurality of laterally extending elements includes at least a wing. 5.The system of claim 1, wherein the plurality of propulsors attached tothe plurality of laterally extending elements are configured to generatea generally upward thrust for the eVTOL aircraft when in the liftposition.
 6. The system of claim 1, wherein the rotation of theplurality of propulsors is configured to generate a generally forwardthrust for the eVTOL aircraft when in the forward thrust position. 7.The system of claim 1, wherein the flight controller comprisesinformation of a preplanned trajectory from vertical flight of the eVTOLaircraft to horizontal flight of the eVTOL aircraft.
 8. The system ofclaim 1, wherein the segmentation boundary includes a first startingsection and a first ending section.
 9. The system of claim 1, whereinthe flight controller comprises a proportional-integral-derivative (PID)controller.
 10. The system of claim 1, wherein the segmented controlalgorithm creates an optimized signal communication as a function of thesegmentation boundary, wherein the optimized signal communicationincludes identifying a discrete timing to transmit the segmentationboundary.
 11. A method for flight control of an electric verticaltakeoff and landing (eVTOL) aircraft, the method comprising:identifying, by a flight controller having a reconfigurable hardwareplatform, the reconfigurable hardware platform containing reconfigurablehardware circuitry, wherein the flight controller is incorporated in anelectric vertical takeoff and landing (eVTOL) aircraft having aplurality of propulsors configured to rotate between a lift position toa forward thrust position, a flight transition point; determining asegmentation boundary of a segmented control algorithm, wherein thesegmentation boundary includes a boundary associated with an ability ofa propulsor of the plurality of propulsors; distributing a plurality ofcommands based on the flight transition point and the segmentationboundary to a cluster of flight controllers, wherein each flightcontroller of the cluster of flight controllers operates a propulsor ofthe plurality of propulsors; performing a flight maneuver based on theplurality of commands, wherein performing the flight maneuver includesperforming a flight transition, wherein the flight transition includes:initiating, by the flight controller, rotation about an axis of thefuselage as a function of the flight transition point; and terminating,by the flight controller, rotation about the axis of the fuselage once adesired flight angle is reached, as a function of the flight transitionpoint.
 12. The method of claim 11 wherein the eVTOL aircraft furthercomprises a pilot override switch.
 13. The method of claim 11 whereineach propulsor of the plurality of propulsors is attached to theaircraft by a rotating actuator.
 14. The method of claim 11 wherein aplurality of laterally extending elements includes at least a wing. 15.The method of claim 11, wherein the plurality of propulsors attached toa plurality of laterally extending elements are configured to generate agenerally upward thrust for the eVTOL aircraft when in the liftposition.
 16. The method of claim 11, wherein the rotation of theplurality of propulsors is configured to generate a forward thrust forthe eVTOL aircraft when in the forward thrust position.
 17. The methodof claim 11, wherein the flight controller comprises information of apreplanned trajectory from vertical flight of the eVTOL aircraft tohorizontal flight of the eVTOL aircraft.
 18. The method of claim 11,wherein the segmentation boundary includes a first starting section anda first ending section.
 19. The method of claim 11, wherein the flightcontroller comprises a proportional-integral-derivative (PID)controller.
 20. The method of claim 11, wherein the segmented controlalgorithm creates an optimized signal communication as a function of thesegmentation boundary, wherein the optimized signal communicationincludes identifying a discrete timing to transmit the segmentationboundary.